Citation
Is It the Right "Fit?" Florida Teachers' Motivations for Choosing a Teaching Career Using the FIT-Choice Scale

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Title:
Is It the Right "Fit?" Florida Teachers' Motivations for Choosing a Teaching Career Using the FIT-Choice Scale
Creator:
Ridgewell, Natalie M
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (335 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Curriculum and Instruction
Teaching and Learning
Committee Chair:
ADAMS,ALYSON JOYCE
Committee Co-Chair:
TERZIAN,SEVAN G
Committee Members:
BONDY,ELIZABETH
MANLEY,ANNE CORINNE
SHELNUTT,KARLA PAGAN

Subjects

Subjects / Keywords:
fit-choice -- florida-teachers -- motivational-theory -- teacher-motivation -- teacher-preparation-programs -- teacher-recruitment
Teaching and Learning -- Dissertations, Academic -- UF
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Curriculum and Instruction thesis, Ph.D.

Notes

Abstract:
Recruitment and retention of high quality and diverse teachers is a continuous dilemma in the U.S. and beyond (Murnane & Steele, 2007; Ravitch, 2010). Research has suggested motivational theory may provide insights into how to better recruit, prepare, and retain effective teachers to address this challenge (Watt, Richardson, & Smith; 2017). The purpose of this quantitative, retrospective exploratory study was to determine what were the initial motivations of in-service Florida K-12 public school teachers to elect teaching as a career, and to determine to what extent teacher characteristics and teacher preparation program characteristics had a relationship to particular motivational factors. Survey research methods used a vetted framework-The FIT-Choice (Factors Influencing Teaching Choice) Scale-one of the landmark conceptual models measuring teacher motivations (Watt and Richardson, 2007). This study extends the literature as it is the first to use the FIT-Choice scale to assess in-service K-12 public school teachers' motivations within the state of Florida, or a similar population. Input was sought from the entire K-12 public-school 2016-2017 teaching population of Florida (N=174,354), resulting in the largest data set yet recorded and analyzed using the FIT-Choice scale (n=8,420). Results indicated, on average, in-service public Florida K-12 public school teachers believed teaching required a high level of expertise, was difficult, had low social status and low monetary compensation; yet, on average, participants reported that teaching had both personal career and societal value. Finally, results indicated the majority of the participants believed they had the capabilities to be a good teacher, and were ultimately satisfied with their choice. This study also adds value to the literature as it examined the extent to which specific teacher and teacher preparation program characteristics had a relationship with particular motivational factor scores. Results indicated that all ten independent variables (teacher and teacher program characteristics) had at least two statistically significant effects across all thirteen dependent variables (motivational factors). There were multiple statistically significant differences amongst genders and specific teacher program characteristics, but little variance with regard to race and ethnicity or between teachers who were categorized as either alternatively or traditionally certified. This study provided baseline data about the motivations that influenced Florida K-12 public school teachers to choose a career in teaching, which might be leveraged to better recruit, prepare, support, and retain teachers in order to meet the diverse educational needs of Florida's schools, students, and teachers. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2018.
Local:
Adviser: ADAMS,ALYSON JOYCE.
Local:
Co-adviser: TERZIAN,SEVAN G.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2019-06-30
Statement of Responsibility:
by Natalie M Ridgewell.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Embargo Date:
6/30/2019
Classification:
LD1780 2018 ( lcc )

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TEACHING CAREER USING THE FIT CHOICE SCALE By NATALIE RIDGEWELL A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FU LFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2018

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2018 Natalie Ridgewell

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husband, Ross; my son, Khoury, my best friend Ashley; and my Socrates, D.R.E. for your unconditional and unyielding love and support and for loving me just the way I am. I love all of you to the moon and back.

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4 ACKNOWLEDGMENTS I would like to thank and acknowledge the followin g for their guidance in support of this dissertation. First and foremost, from the bottom of my heart, I would like to thank my amazing, loving, intelligent, kind, and absolutely beautiful husband, Ross. We have been through so much over the last twelve ye ars. states, two countries, two continents, countless hours of lost sleep, stranded car less, mountains of stress, moments of pure bliss, a wonderful baby boy, massive life changes, and immi nent accurate description of our beautiful life together, except that we must now add Paris and Nice, France to the list (finally!). You have given me uncond itional love and support, and you have the innate ability to make me smile. You always convince me that I can achieve anything I put my mind to, and you keep my feet steadily on the ground. Without your support over the last twelve years I would definitely have lost my sanity many, many, years ago, quit graduate school, and would probably be living in France right now (maybe now you would come with me?) but you gave me a reason to stay. You also gave me and take care of our beautiful baby boy, Khoury. You are the best father and husband anyone could ever ask for, and I love you to the moon and back. Khoury, you will never know what a blessing you are and how much love you have given me ever since the day you were born. he best I would like to thank my best friend, Ashley Hunnicutt. You have provided me with a steadfast friendship for over thirty years, always supporting and always encouraging me every step of the way. You have served as my Chief Editor for anything and everything in print without your sharp eye for grammar and other such talents I surely would have never made it this far. Thank you for our many fun filled adventures and road trips from Panama City, Florida to

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5 Barcelona, Spain, and especially to the magical world of Harry Potter where would I be without that in my life? I am so thankful and grateful we have walked, ran, laughed, cried, and journeyed through this life together through (almost) every stage of o ur lives. You were right younger, because this is where we are, and th at is a long way and so different from where we used to be. You always remind me that I am stronger than I think I am and help me discover joy Godmother to our sweet boy Khoury; Ross and I are all so grateful for the unconditional and unyielding love you give to Khoury. It means more to us than you will ever know. Finally, I very day since then. You are the Bestest best friend, ever. I would like to express my deepest gratitude to Dr. David Evans, (DRE), who, over the sage, confidant, to my dear friend. You made my undergraduate college experience one of the best times of my life and opened my eyes to all of the beauties and complexities of literature, culture, and learning. You helped guide my passion, and I hope that I have made you proud. Without your support, I would not have ever come close to reaching my highest potential. Thank you, and your beautiful, kind, and brilliant wife Ursula McCarty for always having an open door for me, even now, and providing wisdom and guidance every step of the way, especially most could not have a better namesake.

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6 I would like to thank my Chair, Dr. Alyson Adams for your support and guidance through my dissertat ion. I would also like to thank Dr. Sevan Terzian, Dr. Corinne Huggins Manley, and Dr. Elizabeth Bondy who so graciously agreed to participate on my Committee, and tfelt message of thankfulness and gratitude to Dr. Karla Shelnutt who not only served as my External hearted kindred spirit. I would like to give a huge thank you to all of the thousands of amazing Florida public K 12 teachers who took the time to participate in my study and complete probably one of the longest and most in possess, as well as shared, is a wealth of knowledge beyond compare, and I have only begun to scratch the surface Your thoughts, beliefs, and perspectives not only helped me successfully complete my dissertation, but also provided a rare opportunity to explore what motivated so many of you to become teachers. You have a profound effect on the lives of thousands of students across the state of Florida, and I thank you for your commitment, passion, and tenacity. I would like to thank my beautiful family for all of their love and support through the years. I would like to thank my parents and sister Mama, Daddy, and Andrea for your love and support. I know that you have no idea what I have been doing most of the time in graduate school, but you have always wanted the best for me. You have seen me grow and mature throughout the years and have always stood beside me. Mama, you helped motivate me to become a teacher, and you positively changed the lives of hundreds, if not thousands of students over twenty years. I know you are smiling and sen ding your love from Heaven. I love you to the

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7 Thank you, Daddy, for your love thr ough this journey, and for bringing your big, booming laughter and heart into our lives Andrea, we have had so many wonderful memories filled with l aughter, joy, and mischief many tears together, especially over the last few years, but no matter where we go or what life may bring, I will always love and be her grandmother, Mimi (aka General), and grandfather, P pa, who are like second parents to me, and have helped raise me for most of my life. You have not only provided moral and financial support, but also always encouraged me even when you had no idea what in the world I was talking about. Without your help, I could not have continued my education, especially through studying abroad in Paris. I never would have seen Paris the way I was able, allowing me to see the world as I do now. Even though P Pa never believed it possible, and never lived to see it, I am finally going to be finished with school. While I will always be a life long learner, this will be my terminal degree. I promise. Thank you forever for always being there for me. To Sharon, thank you for all of the encouragement and support you have given me over the last year and for opening your heart to our family. To Dr. Natalie King, thank you for walking, supporting, and praying with me through our entire PhD program, starting on day one and continuing even after you left I cannot wait to see your family, and for giving Ross and I the honor of being the Godparents to your beautiful son, To my wonderful Pastors Willie and Linda King: Thank you for constant prayers, love, faith, and leadership through this season Thank you to Dr. Thomasenia Adams

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8 for always being there for me and my family. Your support, logic, and faith have helped us through every kind of obstacle over the past several years I would like to thank Dr. Seluk Dogan for all of your support guiding me through the world of quantitative analysis and having the patience, compassion, and kindness to continually help probably one of the most stubborn peers with whom you have ever collaborated. You and your beautiful family Nihan and Poyraz bring joy and peace into my life. I would also like to thank Dr. Doug Whitaker, whose wit, charisma, intelligence and amazing statistical knowledge this beast of a dissertation. You truly are a gifted statistics teacher! I would like to thank Dr. Diedre Houchen for your mentorship, guidance, love, and support. You are a true tour de force and your strength and resilience are beyond compare. You have the remar kable ability to push there are only a few times in any teacher or her classroom door. I was honored to have the opportunity to be your teacher. I cannot begin to express how proud of and happy I am for you as you enter into your fifth year of teaching, and I l talking, kool confidently say the same, if not more, about you. The student has become the master. You keep doing you, girl. The stars are the limit. I would like to thank Dr. Amanda Gailey, who transitioned from my teacher, Thesis advisor, to Wonder Woman Warrior. You are a master of all an outstanding teacher and

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9 scholar in American literature and Digital Humanities, a fierce social justice advocate, and a wonderful, loving, and kind mother and kindred spirit (and not just to your beautiful children and husband). Thank you for giving me the opportunity to partake in some of your awesome academic adventures and for also sending some of your heartfelt love to me and my family, especially the last two years. You always inspire me, and you are a true Renaissance woman. I would like to thank Dr. Nancy Leech who took a chance to take me on the adventures using the FIT Choice Scale in educational research far beyond my expectations. I am truly grateful for your faith in my abilities and investmen t in my success. I look forward to what the future may bring with our research together. I would also like to thank the staff at the Disability Resource Center, especially Amanda Brown, Beth Roland, and Rick Nelson and Gerry Altamirano, as well as all o f the members of the Ambassadors for Disability Awareness. To my special story tellers Bradley Minotti, a constant advocate for me and I could not have successf ully navigated my program without your assistance, support, and encouragement. Thank you for always reminding me of my strengths and not what others might consider a weakness. Thank you to all of the hundreds of students I have taught over the last sixtee n years from Georgia College & State University, the University of South Carolina, the University of Georgia, the University of Florida, and of course, Peach County High School. It was an honor and pleasure to have the opportunity to teach you and be a par t of your journey. To my first cohort of students at the University of Florida the unforgettable and remarkable Secondary Proteach Program Graduate students as well as my first set of Interns, thank you for making my first semester teaching here such a won derful experience. To my one and only Early

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10 Childhood Education ProTeach Program Cohort of 2017, thank you for opening my eyes and guiding me though your world of childhood learning and development. Khoury will thank you later as well. Joey McGinn, thank y ou for encouraging me to dance again. Tom Scribner, thank you for encouraging me to laugh again, even when life is SNAFU. Sir Thomas Justin grow as a teacher, down to the very last day of class. Remember me when you become POTUS. To the rest of my family and friends, thank you for allowing me to walk down this path and be the beautiful academic nerd that you always knew I could be. And last, but certainly not least, t hank you to God for all of the Grace, love, and guidance Miracles can happen every day and thank you for all of the miracles in my life, especially finishing this degre e. Thank you all for allowing this accomplishment to become possible.

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11 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ............... 4 LIST OF TABLES ................................ ................................ ................................ ......................... 15 LIST OF FIGURES ................................ ................................ ................................ ....................... 16 ABSTRACT ................................ ................................ ................................ ................................ ... 20 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .................. 22 Study Rationale and Overview ................................ ................................ ............................... 23 Background ................................ ................................ ................................ ............................. 31 U.S. Efforts to Increase Teacher Quantity, Quality, and Diversity ................................ 34 The Ebb and Flow of the Teaching Profession: An Historical Perspective .................... 35 An Alternative Approach ................................ ................................ ................................ 37 Improving Teacher Diversity an d Quality in Florida ................................ ...................... 39 Understanding Motivation ................................ ................................ ................................ ...... 40 The Need for (More and Better) Motivational Theory in Teacher Education ........................ 41 Factors Influencing Teacher Choice: The Development of the FIT Choice Conceptual Model and Scale ................................ ................................ ................................ .................. 43 Purpose Statement ................................ ................................ ................................ .................. 47 Research Questions ................................ ................................ ................................ ................. 47 Research Design ................................ ................................ ................................ ..................... 47 Significance ................................ ................................ ................................ ............................ 49 Limitations ................................ ................................ ................................ .............................. 50 Organization of the Dissertation ................................ ................................ ............................. 51 2 LITERATURE REVIEW ................................ ................................ ................................ ....... 53 Motivational Theory ................................ ................................ ................................ ............... 53 Motivational Theory in Education ................................ ................................ .......................... 54 Motivation al Theory in Teacher Education ................................ ................................ ............ 54 The Need for (More and Better) Motivational Theory in Teacher Education ........................ 56 The Four Most Estab lished Motivational Theories ................................ ................................ 58 Self Efficacy ................................ ................................ ................................ .................... 58 Achievement Goal Theory ................................ ................................ .............................. 59 Self Determination Theory ................................ ................................ .............................. 59 Expectancy Value Theory ................................ ................................ ............................... 60 Why EVT? A Summary of Above Theories ................................ ................................ ... 60 Factors Influencing Teacher Choice: The Development of the FIT Choice Conceptual Model and Scale ................................ ................................ ................................ .................. 61 Antecedent Socialization Influences ................................ ................................ ....................... 65

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12 Social Dissuasion ................................ ................................ ................................ ............. 65 Prior Teaching and Learning Experiences ................................ ................................ ...... 66 Social In fluences ................................ ................................ ................................ ............. 67 Proximal Influences ................................ ................................ ................................ ................ 68 Task Perceptions ................................ ................................ ................................ .............. 68 Task dema nd ................................ ................................ ................................ ............ 69 Task return ................................ ................................ ................................ ................ 71 Self Perceptions ................................ ................................ ................................ ............... 72 Values ................................ ................................ ................................ .............................. 73 Intrinsic career value ................................ ................................ ................................ 73 Personal utility value ................................ ................................ ................................ 74 Social utility value ................................ ................................ ................................ .... 75 Fallback Career ................................ ................................ ................................ ................ 78 Outcome: Choice of Teaching Career ................................ ................................ .................... 78 The FIT Choice Survey: Putting Theory to Use ................................ ................................ ..... 80 Other Limitations of Motivation Theory Research in Education ................................ ........... 81 The History, Evolution, and Stagnation of the Teaching Profession ................................ ..... 83 Historical Overview of Teachers and the Profession ................................ ............................. 84 Addressing Teacher Quantity a nd Quality: The Rise of Alternative Routes to Certification (ARCs) in the U.S. ................................ ................................ .................. 87 Certification Pathways ................................ ................................ ................................ 90 Teacher Student Demographic Disparities in the U.S. ................................ ........................... 92 Paths to Becoming a Teacher in Florida ................................ ................................ ................. 95 Chapter Summary ................................ ................................ ................................ ................... 97 3 METHODOLOGY ................................ ................................ ................................ ................. 99 Research Questions ................................ ................................ ................................ ............... 100 Target Population ................................ ................................ ................................ .................. 100 Theoretical Framework ................................ ................................ ................................ ......... 100 Method ................................ ................................ ................................ ................................ .. 103 Data Collection ................................ ................................ ................................ ..................... 104 Survey Responses ................................ ................................ ................................ .......... 106 Participant Demographics ................................ ................................ ............................. 107 Variables and Scales ................................ ................................ ................................ ............. 109 Dependent Variables: Motivational Factors ................................ ................................ .. 109 Influential factors ................................ ................................ ................................ ... 110 Beliefs about teaching ................................ ................................ ............................ 111 Your decision to become a teacher ................................ ................................ ........ 111 Independ ent Variables: Teacher Characteristics and Teacher Preparation Program Characteristics ................................ ................................ ................................ ............ 111 Teacher characteristics ................................ ................................ ........................... 113 Teacher p reparation program characteristics items ................................ ................ 113 Validity and Reliability ................................ ................................ ................................ ......... 114 Construct Validity and Reliability ................................ ................................ ........................ 117 Data Analysis ................................ ................................ ................................ ........................ 121

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13 Research Question 1: Descriptive Statistics ................................ ................................ .. 121 Research Ques tion 2: Multiple Regression Models ................................ ...................... 122 Chapter Summary ................................ ................................ ................................ ................. 128 4 RESULTS ................................ ................................ ................................ ............................. 129 RQ 1: Motivations to Become a Teacher ................................ ................................ ............. 129 RQ 2: Multiple Regression Results ................................ ................................ ...................... 131 Influential Factors ................................ ................................ ................................ .......... 137 Self perceptions of teaching ability (Model 1) ................................ ...................... 138 Intrinsic career value (Model 2) ................................ ................................ ............. 139 Fallback career (Model 3) ................................ ................................ ...................... 142 Personal utility value (Model 4) ................................ ................................ ............. 145 Social utility value (Model 5) ................................ ................................ ................. 147 Prior teaching and learning experience (Model 6) ................................ ................. 149 Social Influence (Model 7) ................................ ................................ ..................... 151 Beliefs About Teaching ................................ ................................ ................................ 153 Expertise (Model 8) ................................ ................................ ................................ 154 Difficulty (Model 9) ................................ ................................ ............................... 156 Social Status (Model 10) ................................ ................................ ........................ 157 Salary (Model 11) ................................ ................................ ................................ ... 159 Decision to Become a Teacher ................................ ................................ ...................... 160 Social Dissuasion (Model 12) ................................ ................................ ................ 161 Satisfaction with Choice (Model 13) ................................ ................................ ..... 165 Chapter Summary ................................ ................................ ................................ ................. 166 5 DISCUSSION AND IMPLICATIONS ................................ ................................ ................ 168 Discussion ................................ ................................ ................................ ............................. 168 Discussion of t he Findings ................................ ................................ ................................ .... 172 Findings Related to RQ1 ................................ ................................ ............................... 172 Findings Related to RQ2 ................................ ................................ ............................... 177 Teacher characteristics ................................ ................................ ........................... 179 Gender ................................ ................................ ................................ .................... 179 Race ................................ ................................ ................................ ............................... 184 Program Characteristics ................................ ................................ ................................ 186 Certification Route ................................ ................................ ................................ ........ 187 Other Teacher Preparation Program Characteristics ................................ ..................... 188 Implications for Future Research ................................ ................................ .......................... 189 Implication and Directions for Future Research 1: Why did Florida K 12 Public School Teachers Want to Become a Teacher in the First Place? ............................... 191 Implication and Directions for Future Research 2: The Paradox of Being Dissuaded, yet Satisfied ................................ ................................ ............................. 193 Implic ation and Directions for Future Research 3: Biases in Hiring Teacher Candidates ................................ ................................ ................................ .................. 194 Implication and Directions for Future Research 4: Beyond Motivations to Become a Teacher: The Motivations to Improve the Educational System .............................. 198

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14 Implication and Directions for Future Research 5 : The FIT Choice as a Predictor for Satisfaction ................................ ................................ ................................ ........... 199 Conclusion ................................ ................................ ................................ ............................ 200 APPENDIX A ADDITIONAL INFORMATION FOR CHAPTER 3: FACTOR LOADINGS AND CFA MODEL DIAGRAMS ................................ ................................ ................................ 204 B ADDITIONA L INFORMATION FOR CHAPTER 3 CORRELATION MATRICES ....... 214 C MULTICOLLINEARITY TESTS, HISTOGRAM, P PLOT, AND SCATTERPLOT DIAGRAMS FOR 13 DEPENDENT VARIABLES ................................ ........................... 218 D TEACHER CHARACTERISTICS AND DEMOGRAPHICS ................................ ............ 244 E ADDITIONAL INFORMATION FOR CHAPTER 4: FULL REGRESSION OUTPUTS FOR ALL 13 VARIABLES ................................ ................................ .............. 252 F FINAL FIT CHOICE SURVEY ................................ ................................ .......................... 265 ................................ ................................ ................................ ............ 315 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ....... 335

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15 LIST OF TABLES Table page 3 1 Demographics of Participants ................................ ................................ .......................... 108 3 2 The FIT Choice Scale: factors, it .. 118 3 3 Goodness of fit statistics for measurement invariance model across alternatively and traditionally certified group ................................ ................................ ............................. 120 4 1 Descriptive Statistics: Mean Scores and Standard Deviations ................................ ........ 130 4 2 Regression Analysis: Statistically Significant Predictors of Self perception s of Teaching Ability ................................ ................................ ................................ .............. 138 4 3 Regression Analysis: Statistically Significant Predictors of Intrinsic Career Value ....... 139 4 4 Regressi on Analysis: Statistically Significant Predictors of Fallback Career ................. 142 4 5 R egression Analysis: Statistically Significant Predictors of Personal Utility Value ....... 145 4 6 Regression Analysis: Statistically Significant Predictors of Social Utility Value ........... 147 4 7 Regression Analysis: Prior Teaching and Learning Experiences ................................ .... 149 4 8 Regression Analysis: Statistically Significant Predictors of Social Influences ............... 151 4 9 Regression Analysis: Statistically Sig nificant Predictors of Expertise ............................ 154 4 10 Regression Analysis: Statistically Significant Predictors of Difficulty ........................... 156 4 11 Regress ion Analysis: Statistically Significant Predictors of Social Status ...................... 157 4 12 Regression Analysis: Statistically Significant Predictors of Salary ................................ 159 4 13 Regression Analysis: Statistically Significant Predictors of Social Dissuasion .............. 161 4 14 Regression Analysis: Statistically Significant Predictors of Satisfaction with Ch oice ... 165 5 1 Descriptive Statistics: Mean Scores and Standard Deviations ................................ ........ 172 5 2 Mean Scores and Standard Deviations of In Service Teachers within the U.S. .............. 175

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16 LIST OF FIGURES Figure page 1 1 FIT Choice Conceptual Model. ................................ ................................ ......................... 44 2 1 FIT Choice Conceptual Model ................................ ................................ .......................... 97 4 1 Variables and levels associated with higher motivational scores. ................................ ... 135 4 2 The positi ve and negative slopes of variables that had a statistically significant relationships ................................ ................................ ................................ ..................... 136 5 1 Motivational Factors and the corresponding number of statistically significant relationship with e ach motivational factor score: ................................ ............................ 178 A 1 Scale I Influential Factors About Teaching Models Fit. ................................ .................. 204 A 2 Scale II Beliefs About Teach ing Models Fit. ................................ ................................ ... 205 A 3 Scale III Decision to Become a Teacher Model Fit ................................ ....................... 205 A 4 CFA Model Diagram: Self perceptions of Teaching Ability. ................................ ......... 206 A 5 CFA Model Diagram: Intrinsic Career Value. ................................ ................................ 206 A 6 CFA Model Diagram: Personal Utility Value. ................................ ................................ 207 A 7 CFA Model Diagram: Social Utility Value. ................................ ................................ .... 208 A 8 CFA Model Diagram: Prior Teaching and Learning Experiences. ................................ .. 209 A 9 CFA Model Diagram: Social Influence. ................................ ................................ .......... 209 A 10 CFA Model Diagram: Task Difficulty. ................................ ................................ ............ 210 A 11 CFA Model Diagram: Task Expertise. ................................ ................................ ............ 210 A 12 CFA Model Diagram: Social Status. ................................ ................................ ............... 211 A 13 CFA Model Diagram: Social Dissuasion. ................................ ................................ ........ 212 A 14 CFA Model Diagram: Satisfaction with Choice. ................................ ............................. 212 A 15 CFA Model Diagram: Salary. ................................ ................................ .......................... 213 B 1 Ability Inter Item Correlation Matrix ................................ ................................ .............. 214 B 2 Intrinsic Inter Item Correlation Matrix ................................ ................................ ............ 214

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17 B 3 Fallback I nter Item Correlation Matrix ................................ ................................ ........... 214 B 4 Job Security Inter Item Correlation Matrix ................................ ................................ ..... 214 B 5 Time for Family Inter Item Correlation Mat rix ................................ ............................... 215 B 6 Job Transferability Inter Item Correlation Matrix ................................ ........................... 215 B 7 Personal Utility Value Inter Item Correlation Matrix ................................ ..................... 215 B 8 Shape future of Children/Adolescents Inter Item Correlation Matrix ............................. 215 B 9 Enhance Social Equity Inter Item Correlation Matrix ................................ ..................... 215 B 10 Make Social Contribution Inter Item Correlation Matrix ................................ ................ 216 B 11 Work with Children/Adolescents Inter Item Correlation Matri x ................................ .... 216 B 12 Social Utility Value Inter Item Correlation Matrix ................................ ......................... 216 B 13 Prior Teaching & Learning Experiences Inter Item Correlatio n Matrix ......................... 216 B 14 Social Influences Inter Item Correlation Matrix ................................ .............................. 216 B 15 Expertise Inter Item Correlation Matrix ................................ ................................ .......... 217 B 16 Difficulty Inter Item Correlation Matrix ................................ ................................ ......... 217 B 17 Social Status Inter Item Correlation Matrix ................................ ................................ .... 217 B 18 Social Dissuasion Inter Item Correlation Matrix ................................ ............................. 217 B 19 Satisfaction with Choice Inter Item Correlation Matrix ................................ .................. 217 C 1 Tests for Multicollinearity, Ability. ................................ ................................ ................. 218 C 2 Histogram, P Plot, and Scatterplot for Ability ................................ ................................ 219 C 3 Tests for Multicollinearity, Intrinsic Career Value. ................................ ......................... 220 C 4 Histogram, P Plot, and Scatterplot for Intrinsic Career Value ................................ ........ 221 C 5 Tests fo r Multicollinearity, Fallback Career. ................................ ................................ ... 222 C 6 Histogram, P Plot, and Scatterplot for Fallback Career ................................ .................. 223 C 7 Tests for Multicollin earity, Personal Utility Value. ................................ ......................... 224 C 8 Histogram, P Plot, and Scatterplot for Personal Utility Value. ................................ ....... 225

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18 C 9 Tests for Multicoll inearity, Social Utility Value. ................................ ............................ 226 C 10 Histogram, P Plot, and Scatterplot for Social Utility Value. ................................ ........... 227 C 11 Tests for Multicoll inearity, Prior Teaching and Learning Experiences. .......................... 228 C 12 Histogram, P Plot, and Scatterplot for Prior Teaching and Learning Experiences. ........ 229 C 13 Tests for Multicollinearity, Social Influences. ................................ ................................ 230 C 14 Histogram, P Plot, and Scatterplot for Social Influences. ................................ ............... 231 C 15 Tests for Multicollinearity, Expertise. ................................ ................................ ............. 232 C 16 Histogram, P Plot, and Scatterplot for Expertise. ................................ ............................ 233 C 17 Tests for Multicollinearity, Difficulty. ................................ ................................ ............. 234 C 18 Histogram, P Plot, and Scatterplot for Difficulty. ................................ ........................... 235 C 19 Tests for Multicollinearity, Social Status. ................................ ................................ ........ 236 C 20 Histogram, P Plot, and Scatterplot for Social Status. ................................ ...................... 237 C 21 Tests for Multicollinearity, Salary. ................................ ................................ .................. 238 C 22 Histogram, P Plot, and Scatterplot for Salary. ................................ ................................ 239 C 23 Tests for Multicollinearity, Social Dissuasion. ................................ ................................ 240 C 24 Histogram, P Plot, and Scatterplot for Social Dissuasion. ................................ .............. 241 C 25 Tests for Multicollinearity, Satisfaction with Choice. ................................ ..................... 242 C 26 Histogram, P Plot, and Scatterplot for Satisfaction with Choice. ................................ .... 243 D 1 District Name respondents (Alachua Lee) ................................ ................................ ....... 244 D 2 District Name respondents (Leon Walton) ................................ ................................ ...... 245 D 3 District Name respondents bar chart ................................ ................................ ................ 246 D 4 Military respondents ................................ ................................ ................................ ........ 246 D 5 Military respondents bar chart ................................ ................................ ......................... 246 D 6 Base salary ................................ ................................ ................................ ....................... 247 D 7 Base salary bar chart ................................ ................................ ................................ ........ 247

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19 D 8 Geographical Breakdown ................................ ................................ ................................ 248 D 9 Geographical Breakdown bar chart ................................ ................................ ................. 248 D 10 Title 1 school respondents ................................ ................................ ............................... 249 D 11 Title 1 school respondents bar chart ................................ ................................ ................ 249 D 12 Degree level ................................ ................................ ................................ ..................... 250 D 13 Degree level bar chart ................................ ................................ ................................ ...... 250 D 14 Route to Certification ................................ ................................ ................................ ....... 251 D 15 Route to certification bar chart ................................ ................................ ........................ 251 D 16 Teacher preparation program recruitment bar chart ................................ ........................ 251 E 1 Regression Output for Self Perceptions of Teaching Ability. ................................ ......... 252 E 2 Regression Output for Intrinsic Career Value. ................................ ................................ 253 E 3 Regress ion Output for Fallback Career. ................................ ................................ ........... 254 E 4 Regression Output for Personal Utility Value ................................ ................................ 255 E 5 Regression Output for Social Utility Value ................................ ................................ ..... 256 E 6 Regression Output for Prior Teaching & Learning Experiences ................................ ..... 257 E 7 Regression Output for Social Influences ................................ ................................ ......... 258 E 8 Regression Output for Expertise ................................ ................................ ...................... 259 E 9 Regression Output for Difficulty ................................ ................................ ..................... 260 E 10 Regression Output for Social Status ................................ ................................ ................ 261 E 11 Regression Output for Salary ................................ ................................ ........................... 262 E 12 Regression Output for Social Dis suasion ................................ ................................ ........ 263 E 13 Regression Output for Satisfaction with Choice ................................ .............................. 264

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20 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy TEACHING CAREER USING THE FIT CHOICE SCALE By Natalie Ridgewell December 2018 Chair: Alyso n Adams Major: Curriculum and Instruction Recruitment and retention of high quality and diverse te achers is a continuous dilemma in the U.S. and beyond (Murnane & Steele 2007; Ravitch, 2010). Research has suggested m otivational theory may provide insight s into how to better recruit, prepare, and retain effective te achers to address this challenge (Watt, Richardson, & Smith; 2017). T his purpose of this quantitative retrospective exploratory study was to examine the initial motivations of in service Florid a K 12 public school teachers to elect teaching as a career, as well as explore the extent to which certain teacher characteristics and teacher preparation program characteristics had a relationship to particular motivational factors. S urvey research meth ods were grounded in an adapted Expectancy Value Theory model using a vetted framework The FIT Choice (Factors Influencing Teaching Choice) Scale and Survey one of the landmark conceptual models measuring teacher motivations (Watt and Richardson, 2007 ). Th is study extends the literature as it is the first to use the FIT Choice scale to assess in service K similar population. Input was sought from t he entire K 12 pu blic school 2016 2017 teaching population of Florida ( N = 174,354 ), resulting in the largest data set yet recorded and analyzed using the FIT Choice scale ( n =8,420). Findings suggest, on average, in service public Florida

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21 K 12 public school teachers believed teaching required a high level of expertise, was difficult had low social status and low monetary compensation; yet on average, participants reported that teaching had both personal career and societal value. Finally, results indicated the majority of the participants beli eved they had the capabilities to be a good teacher and were ultimately satisfied with their choice. T his study also adds value to the literature as it reveals the extent to which specific teacher and teacher preparation program characteristics had a rela tionship with particular motivational factor scores. Results indicate d that all ten independent variables (teacher and teacher program characteristics) had at least two statistically significant effects across all thirteen dependent variables (motivational factors). There were multiple statistically significant differences amongst genders and specific teacher program characteristics, but little variance with regard to race and ethnicity or between teachers who were categorized as either alternatively or tra ditionally certified. While this study was largely exploratory, it provided baseline data about the mo tivations that influenced Florida K 12 public school teachers to choose a career in teaching, which might be leveraged to better recruit, prepare, suppor t, and retain teachers in order to meet the diverse educational needs of Florida

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22 CHAPTER 1 INTRODUCTION a chef's technique is, I would proba Jacques Ppin Jacques Barzun In almost every cuisine around the world, one would be hard pressed not to find an omelet recipe. There are many variations of this ubiquitous, beaten egg based dish from the American Southwest omelet, Chinese egg foo young Italian frittata Japanese tamagoyaki omelette While acknowledging the differences in origin, each dish usually shares a common element. In most versions several eggs are beaten; the egg mixture is heated in a pan or dish; and salt, pepper, and/or select ingredients are added to taste. On the surface, from the perspective of someone unfamiliar with cooking, omelets may appear to be a cheap, simple, straig htforward, and perhaps even an unimpressive dish. However, as anyone who is an avid practitioner or expert in cuisine knows, omelets are nothing of the sort (Bourdain, 2010). For years, Jacq u es Ppin continually declared cooking a good omelet is o ne of the hallmarks of determining a good chef as indicated in the quote above In the classic cookbook, Mastering the Art of French Cooking holle, & Child, 1964, p. omelettes proceeding twelve pages in her book, describes in great detail how to make a delicious dish that can, if executed properly, be made in less than one minute (Beck, Bertholle, & Child, 1964, p. 123). travel documentarian declared, he way you make an omelet reveals your character 1). Making a good omelet is deceptively difficult, requiring a great deal of expertise, technique,

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23 patience, experience, and dedication. One could easily say the same thing about being a good teacher. One might wonder how the desire to create a great omelet is connected t educational dilemma of increasing and improving teacher quality, but after a closer examination the analogy might not appear so disparate. Many Americans love to eat omelets and even love lecting their favorite fillings. However, unless they possess a certain level of cooking expertise there are many Americans who simply disregard, or are unaware of, the adept skills, techniques, expertise, and desire needed to create a great omelet. Simil arly, because the quality of education in America has been a plague on every facet of society over the last three decades (Ravitch, 2010; Carter & Welner, 2013), many Americans love to discuss and critique what makes a great teacher, create a distinctive s et of characteristics or standards that effective teachers should possess and outcomes teachers should produce, while simultaneously disregarding, or remaining nave to the adept skills, techniques, expertise, and desire needed to become not just a teacher but a great teacher. Study Rationale and Overview Most Americans want a high quality public education system (Berry, 2013; National Research Council, 2010). However, controversy surrounds the decision about the best path to take to achieve this goal, th e type of teachers who will implement these reforms, and the best way to prepare them for the challenging task at hand. Education reform has been debated across many spectrums of American society in conversations about politics, economics, culture, nationa l security, and even morality. The declining quality of American education has impacted so many aspects of society, especially over the last three decades: cultural enrichment, human capital, economic stability, disparities of wealth and poverty, global co mpetitiveness, and even national security; subsequently both the public and private spheres have invested billions of

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24 on Billings, 2013; Ravitch, 2010 ). A myriad of variable s all contribute to what makes students successful, but r esearch repeatedly has suggested that effective teachers are one of the most critical resources needed to improve the quality of education, (Berry, 2013; Darling Hammond 2010, 2013; Ingersoll, 2007 ; Koz o l, 1991; K umashi ro, 2010 ; Murnane & Steele, 2007; Ravitch, 2010). The knowledge, skills, dispositions, and characteristics teachers possess are often associated with student achievement, and teacher preparation rout es and programs are often associated with both Berry, 2013; Darling Hamm ond, 2010, 2013; Ingersoll, 2007 ; Koz o l 1991; Kumashi ro, 2010 ). Consequently significant efforts and resources from teacher education program, communit ies, private enterprise to the state and federal government retaining effective teachers and principals, especiall Department of Education, 2009, p. 2). Despite the myriad initiatives and investment, the efforts to increase both the quantity, quality and effectiveness of teachers have not resulted in the success desired (Darling Hammond, 2010, 2013; NCATE, 2010; U.S. Department of Education, 2009 ). On e potential shortfall of prior efforts is that the motivational factors that influenced people to become teachers in the first place may not have been taken into consideration when developing such initiatives. In other areas of teacher education research, practicing teachers, as well as preservice teachers are being included in the research efforts to improve the state of teacher preparation and professional development (Dana & Yendol Hoppey, 2008 2009 ; Zeichner, 2013a ). As Zeichner (2013a ) t for teacher knowledge and teacher voice can be brought about in different ways, but appears to be essential to a transformational teacher

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25 through the lack of res earch on their motivations. Many researchers posit that motivational theory can provide critical insights as to how to better recruit, prepare, and retain effective teachers by examining their aspirations, beliefs, values, and experiences as they relate to their role (Akar, 2012; Butler, R., 2014 ; Fokkens Bruinsma & Canrinus, 2012; Heinz, 2015; Kaplan, 2014; Leech & Haug, 2015; Leech, Haug, & Bianco, 2015; Lin et al., 2012; Richardson & Watt, 2007 2016 ; Richardson, Karabenick, & Watt, 2014; Roth, 2014; Wat t & Richardson, 2006, 2012). As Heinz (2015) states, student teacher motivations offer an insight into the factors that attract individuals to teaching, which, in turn, may influence how long they may remain in their initial preparatory courses and the pr ofession, and the nature and extent of their engagement with (or concentration on) their course, and their teaching roles and responsibilities. (p. 259) Until the last decade, there has been a limited amount of high quality empirical research on both the u se of, and potential for, motivational theory in teacher education ( Butler, R., 2014 ; Heinz, 2015; Kaplan, 2014; Leech & Haug, 2015; Leech, Haug, & Bianco, 2015; Richardson & Watt, 2007 2016 ; Richardson, Karabenick, & Watt, 2014; Roth, 2014; Watt & Richar dson, 2006, 2012). Dating as far back as the 1960s, researchers claimed there was a need to better understand the beliefs, values, knowledge, motivations, expectations, and experiences that teacher candidates bring to their roles as future educators and ho w that knowledge could affect teacher performance, teacher development, and even impact student performance (Brookhart & Freeman, 1992; Richardson, Karabenick, & Watt, 2014; Watt & Richardson, 2006; 2007; Watt, Richardson, & Smith, 2017; Watt et al., 2012) In a meta study of teacher motivational research research that generates descriptions of trends rather than static profiles of entering teacher sh an evidence based foundation from which to build (p. 54). Despite this

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26 recognition of the necessity to better understand what motivates individuals to choose teaching as a career, many researchers claim there has not been consistency among design, theor y, (Heinz, 2015; Richardson & Watt, 2007 2016 ; Richardson, Karabenick, & Watt, 2014; Watt & Richardson, 2006, 2012; Watt, Richardson, & Smith, 2017). There has be en a recent resurgence in higher quality motivational theory research in teacher education, thanks in part to one of the landmark conceptual and methodological models and scales by which to guide the measurement and analysis of the initial motivational fac tors to (Factors Influencing Teaching) Choice Scale ( Butler, R., 2014 ; Heinz, 2015; Kaplan, 2014; Leech & Haug, 2015; Leech, Haug, & Bianco, 2015; Leech, Haug, Ridgewell, & Ruben, 2018; Richard son & Watt, 2006, 2007 2016 ; Richardson, Karabenick, & Watt, 2014; Roth, 2014; Watt & Richardson, 2006, 2012; Watt, Richardson, & Smith, 2017). Richardson, Karabenick, and Watt (2014) argue that to healthy, committed, and effective teachers, it is first necessary to understand initial motivations to choose a career in teaching (p. xiv ). Without doing so, the ability to leverage the full power of motivational theory, and how it can impact both teach er and potential student success will be limited in both breadth and depth. Given the necessity to increase the quantity, quality, and diversity of the teaching population locally, nationally and internationally the knowledge base formed from the intersect ionality of motivational theory and teacher education research needs to be strengthened. However, due to many of its unique attributes, the nature and application of motivational theory research in the United States is required to a different extent than m any other countries, specifically as it relates to using the FIT Choice Scale Returning to the omelet analogy, the

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27 array of ingredients and techniques required to create not just one type, but multiple versions of satisfying and delicious omelets is key. The ability to please the varied American palate with regard to both different tastes and cultures is what makes the difference between any chef and a great chef Similarly, teachers are constantly trying to satisfy many varied needs, but the skills necess ary to do so, and motivation required to undertake such a task are often not appreciated when considering what it takes to create, support, and retain not just any teacher, but a great teacher. As compared to other settings and populations, the American e ducational landscape is unique in that it has an ever increasingly diverse student population juxtaposed with an unchanging homogeneous teacher population. The addition of a plethora of opportunities beyond traditional, u niversity based programs to become a teacher, as well as the disparities in health, education, income, and human development shine a spotlight on the many variables at play with regard to educational quality and assessment (Feistritzer, 2005; National Research Council, 2010; Social Science Research Council, 2014; U.S. Census Bureau, 2016). While it is important represented groups to teacher motivations of potential and actual initial teacher education applicants from different socio Heinz, 2015, p. 274). This wealth of information can ultimately be used to inform policy makers, teacher preparation programs, and other educational stakeholders as to how to better recruit, prepare, support, and retain effective teachers. Therefore, this purpose of this quantitative retrospective exploratory study was to examine the initial motivations of in service Florida K 12 public s chool teachers to elect teaching as a career, as well as explore the extent to which certain teacher characteristics and

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28 teacher preparation program characteristics had a relationship to particular motivational factors. To date, there have only been a hand ful of studies within the United States to use the FIT Choice model and scale, only three of which have included samples of in service teachers: Leech and Haug (2015), Leech, Haug, and Nimer (2015), and Leech, Haug, Ridgewell, and Ruben (2018). Therefore, I sought to expand the FIT Choice literature through a quantitative research study that was both exploratory and retrospective in nature. It was exploratory because there are not sufficient theories or literature on which to build the design, methods, or a nalysis specific to the context or sample population of my study Florida K 12 public school teachers. Additionally, I examined correlational relationships among important constructs in teacher motivations, and I was neither attempting to control or manipul ate the variables in this study or experiences. My study was retroactive because I asked in service Florida public K 12 teachers to reflect upon their past motivations for choosing a career in teaching. Florida was a prime setting to co nduct an exploratory, retrospective study because none of the previous FIT Choice samples or settings have had the level of diversity that is represented in the state of Florida with regard to either teacher or teacher preparation characteristics. D ue to s imilar characteristics between Florida and the United States, Florida could be viewed as a type of microcosm of the U.S. Some similarities between Florida and the U.S. at large were: 1. The diversity in demographics and cultures (U.S. Census Bureau, 2016) 2. C omparable health, education, and income, and human development indices (Social Science Research Council, 2014; Human Development Report, 2017) 3. The number and array of teacher preparation programs U.S. 675 vs. FL 433 ( NCES, 2018 ; Jacobs, 2017) 4. Florida is the 3rd most populous state in the na tion (U.S. Census Bureau, 2016)

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29 I not only measured motivations of in service public K 12 Florida teachers, but also teachers who were certified through a Traditional Route to Certification ( TRC) as well as an Alternative Route to Certification (ARC). However, any comparisons between the existing in service studies and my study should be made with restraint, as these previous studies were conducted in a Western state that is very homogeneous ( with regard to both teacher and teacher program characteristics) and ha d sample sizes that were small ( between 150 and 250 participants ) Currently study is the only one which has reported to have included both in service te achers who completed a university based or traditional routes to certification, as well as alternative route to certification. However, just 1.7% of the sample (n=4) completed an ARC, but that percentage was reflective of the teaching population of that st ate. Approximately 30% of the teacher population in the U.S., as well as the teacher population in Florida, are alternatively certified ( NCES, 2018 ; Jacobs, 2017). If one were to study only the motivations of preservice teachers enrolled in TRCs, then almo st one third of the teaching workforce would potentially be omitted from the literature base. Findings from my study, and future studies, could ultimately be used to inform policy makers, teacher preparation programs, and other educational stakeholders as to how to better recruit, prepare, support, and retain effective teachers within the state of Florida. With reference to the two introductory quotes of this chapter, the esteemed chef and restaurateur Jacques Ppin (1985), declared that the art of omelet m aking was often underestimated, and the esteemed educational historian and philosopher Jacques Barzun (1945) declared the art of teaching had been disregarded. While these quotes are cited frequently nd the latter half has a direct impact on the context of my study. T

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30 teachers, but to recognize the good ones and not discourage them before they have done their 1) teaching is not highly valued or regarded, 2) supplying enough teachers is not a problem, but 3) recognizing and en couraging teachers is a problem I agree that the first and third claims are still accurate today, but I respectfully dispute the second. Supplying enough teachers is a problem currently faced by the U.S., as well as Florida, specifically as it relates to m eeting the needs of an extremely heterogeneous student population with diverse needs. Myriad K 12 pathways, such as voucher programs, charter schools, alternative schools, for profit schools, in home schools, and other non ecame increasingly popular during the 1980s and 1990s (Ravitch, 2010). The diverse places and spaces in which K 12 students are educated are mirrored by the aforementioned plethora of teacher preparation programs in the U.S. and Florida 675 and 433 respect ively (FL Dept. of Education, 2015; Jacobs, 2017; U.S. Dept. of Education, 2015). During the last two decades, for alternatives to public education. Furthermo re, when Jacques Barzun published his book in 1945, many teachers and students in American public schools were more demographically and culturally homogeneous (and also still segregated) (Tyack, 1974 ). Additionally, the majority of the American K 12 public school teaching staff was and continues to be relatively homogeneous comprising predominately of White, Middle class, English speaking, Protestant, heterosexual, able bodied females while the American K 12 public school student body continues to represe nt an increasingly diverse student population ( NCES, 2018 ; Jacobs, 2017; Spring, 2016; U.S. Department of Education et al, 2016 ). Therefore, due to the demographic and

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31 cultural dissonance that currently exists between teachers and students, there is a need for not only more teachers in the U.S., but a specific need for more high quality, diversified, and inclusive teachers who can meet the ever changing needs of American students ( NCES, 2018 ). ed to be addressed, because while these are new dilemmas within the realm of teacher recruitment, there remains the challenge of appreciating, supporting, emboldening, and subsequently retaining the excellent teachers who are currently in the field. Almos t seventy years later, at the 23rd Annual Benjamin E. Mays Lecture in Atlanta achers and schools who have and continue to address and eliminat e many educational challenges in America, but they are too few and too often both unrecognized it is necessary to keep teachers motivated and dedicated to continue the work they do Similar to a novice chef who believes, like so many people, that the omelet is a simple and unsophisticated dish, our society does not truly seem to understand what the profession of teaching as a whole entails, what is required to prepare future teacher s to support children more effectively, and that this is aspirations for becoming teachers can provide insights into what supports, skills, structures, and resources are necessary to recruit, prepare, and retain effective teachers, especially given the high demands and requirements of the profession. Background The need for more and better teachers is a global issue, as highlighted in the Agenda for Sustainable Develo pment set forth by the UN Summit in November 2015. Over 150 countries united to adopt this agenda as well as the corresponding 17 Sustainable Development Goals

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32 ( Un ited Nations General Assembly 2015 ). Importantly, as related to the context of this study, lifelon United Nations General Assembly 2015 ). However, the estimated number of teachers required to reach this goal is daunting: According to the UNESCO Institute for Statistics (UIS) almost 69 million teachers must be recruited across the globe, to not only provide every child with primary and secondary education but also recruit more qualified teachers ( United Nations General Assembly 2015 ). Over the last four decades in many areas around the world, there has been a steady decrease in the number and quality of people entering the profession, crea ting a teacher shortage (Lin et al., 2007; Murnane & Steele, 2007; NCES, 2014, United Nations General Assembly 2015 ; Zeichner, 2003 b ). The U.S. is no exception as exhibited by the No Child Left Behind mandates that resulted from the No Child Left Behind Act of 2001 and what would ultimately define and teacher (Ravitch, 2010). Currently, there are over 3.6 million public K 12 school teachers in the United States who are charged with the daunting task of preparing the next generation of students to restore the economy of the United States to compete in the 21st Century global market, while typically working long hours with little financial compensation, low social status, and limited autonomy. Over the last two centuries, their roles and responsi bilities in American society have ebbed and sitters, social workers, career and vocational trainers, cultural reformers, warriors, to protectors of the global economy (Bailyn, 19 60; Kaestle, 1983; Nash 2005; Spring, 2014). As the positions of teachers evolved, so too has the professionalization of the career, especially regarding social status, gender roles, compensation, certification and education requirements, and collective g oals of the

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33 professorate, as well as gun safety (Spring, 2014 ; Darling Hammond 2010, 2013 ). The issue of school safety is of utmost importance in the current climate, as evidenced by the recent events occurring in Parkland, Florida. Given the extremely hi gh risk and responsibility of taking on this challenge, and the unknown level of potential of reward outside of compensation, the critical question arises: Why teach? The reasons for the lack of high quality teachers, and in many cases, the lack of teache rs in general, are varied. The aging of the teaching force, the subsequent high number of retirees, and high attrition rates among all ages are large contributors (Boyd et al ., 2011; Cochran Smith & Zeichner, 2005; Darling Hammond, 2010; OECD, 2011; Zeichn er, 2003 b ) Moreover, the teaching profession is often perceived as having low social and occupational status, with little compensation for an often difficult and demanding job (Darling Hammond & Bransford, 2005, Darling Hammond et al ., 2005; Ingersoll, 20 07 ; Ladson Billings, 2013), while also having complex and delayed hiring practices ( Krasnoff, 2014 ; Levin & Quinn, 2003). The combination of all these factors suggests teaching may not be an attractive, rewarding, or sustainable career, as evidenced by the steady decline of people majoring in education: In 1971, of the 839,730 Bachelor degrees awarded in the U.S., 21% were in education. That number has continued to decrease, with just 98,900 (5%) deg rees awarded in 2014 (NCES, 2001 ; 2014). Compounding the d ilemma of the lack of qualified teachers is the continuous problem with the recruitment, education, preparation, and retention of motivated, committed, high quality teachers in the U.S. (Darling Hammond, 2010; Darling Hammond, Wei, & Johnson, 2009; Ingerso ll, 2007; Krasnoff, 2014 ; Sinclair, 2008; Zeichner, 2003 b ). Ultimately, it will cost America alone more (in both human and financial capital) to ignore the teacher shortage (in quantity and quality) than it would to rectify the situation (Belfield & Levin, 2013; Ladson Billings, 2013).

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34 U.S. Efforts to Increase Teacher Quantity, Quality and Diversity By the mid 1980s, the teaching profession was projected to experience a teacher shortage of over two million teachers within the next two decades (Feistritzer 2005; Johnson, Birkeland, & Peske, 2005). 1 Teacher preparation programs at colleges and universities, which are now usually referred to as traditional routes to certification (TRCs), strived to not only increase the number of teachers, but also combat th e negative stigma surrounding public education and teacher quality. While there were guidelines established through the No Child Left Behind Act, many education researchers took issue with those definitions, and proceeded to define high quality teachers wi th other attributes. These researchers defined a high quality teacher as being culture, and types of abilities. Researchers also claimed e xceptional teachers should have a deep understanding of the subject area content that they teach and should participate in professional development on a regular basis to stay up to date on the latest developments in the field They continued to state that a high quality teacher should then be able to take that content knowledge and determine the best way for students to learn; a great teacher needs to know how to teach just as much as he or she knows what to teach. The ability to make formative assessments, continuously differentiate instructio n, practice appropriate culturally responsive teaching and support each child in reaching his or her highest potential is a comp lex process that never ends, and is a true sign of a high quality teacher, according to these education researchers (Darling Ham mond, 2010; Darling Hammond, 2013 ; Hayes & Jurez, 2012 ; Siddle Walker, 2011) 1 It is no w clear that many of those projections were based on misleading statistics, and the crisis never fully hit all areas of the U.S. (Darling Hammond, 2000; Feistritzer, 2005; Johnson, Birkeland, & Peske, 2005).

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35 Therefore, teacher preparation programs often made programmatic changes in order better prepare their teacher candidates to meet the needs of K 12 students before entering the w orkforce, while simultaneously addressing the increasing teacher shortage ( Ingersoll, 1999; Kumashiro, 2010 ). In an effort to improve the quality of education, teacher education programs began to instill alterations such as extended clinical experiences wi th closely integrated coursework, core curriculum taught in context of practice, and creating strong relationships among school and university stakeholders ( Darling Hammond, 2010 ; Darling Hammond, 2013; Darling Hammond & Bransford, 2005; Ingersoll, 1999; N CATE, 2010). The E bb and F low of the T eaching P rofession: An H istorical P erspective However, education programs still endeavored to improve the quality and increase the quantity of teachers and these programs faced increasing scrutiny by both the public and private spheres. Historically, as education became more centralized and bureaucratic, teachers, especially female instructors, felt devalued. During the 1940s, schools were criticized for being economy and the atomic age. In the Additionally, in the late 1950s and early 1960s, the Cold War and the Civil Rights movements created tensions both inside and outside the classroom regarding the Space Race, the fear of Communism, and the overall safety of the nation (Laats, 2010; Ravitch, 2010; Rudolph, 2002). Concurrently, many females either returned to, or joined the teaching profession during this time. Desp ite their enormous contribution to the economic health and stability of the nation during both World War I and especially World II, once American servicemen returned from overseas, readjust to the roles of housewives and mothers or to careers such as antiquated gender norms resurfaced (Ryan & Terzian, 2009, p. 77). This increased feminization of the profession only decreased the social status of the

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36 profession (Ahwee et al., 2013; Apple, 2013; Bra ndmo & Nesje, 2017; Jackson, 2013; Nash, 2005) Additionally, the 1960s and 1970s saw an even greater increase in federal involvement in public education 2 especially with regard to the legislation put in place as part of President responsibility of schools and teachers versus the responsibility of American citizens and government. The cognitive dissonance that filled American society transferred into the classroom immigrants, non Protestants, and other minorities began to protest the oppression of their cultures and beliefs in public schools where their children were forced to assimilate to Ame rican middle class White Anglo Saxon Protestant (WASP) values. Due to their low prestige and educational stakeholders (ranging from parents to politicians) who usurped on educational reform; and two, from the increasing use of textbooks, both of which began to dictate not only what was taught in classrooms, but also how to teach as well (Zimmerman, in instruction between the 1930s and the new wave of federal initiatives following the 1970s ignited even more federal involvement and oversight, beginning with the creation of the Federal Department of Education signed by President Jimmy Carter on October 17, 1979. The publication of A Nation at Risk in 1983, a report completed by the National Commission on Excellence in Education, contained sections 2 Examples include the Civil Rights Act (1964), the Voting Rights Act (1965), the creation of the Head Start Program (1965), and the Elementary and Secondary Education Act, (1965), and Education for All Handicapped Children Act (1975)

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37 that exposed academic deficienc ies of American public schools (National Commission on Excellence in Education, 1983). A Nation at Risk gained enormous publicity and prominence both inside and outside the field of education, and unfortunately, instead of looking outsid e the school walls to examine what social and systemic elements could be causing the academic discrepancies, the majority of Americans pointed their fingers at public schools and teachers. Public education in America continued to be crucified during the 19 80s and 1990s, with teachers and their preparation programs bearing the brunt of the blame (Ravitch, 2010). An Alter native A pproach Despite the resulting programmatic changes made in TRC programs, legislators and policy makers still felt the pressure to ad dress both the number and quality of teachers (Imig & Imig, 2008) and during the 1980s, subsequently began to alter and enact regulations governing what made it more flexible with regard to how one could become certified to teach (Feistritzer, 2005; Johnso n, Birkeland, & Peske, 2005). One consequence of these changed regulations was the establishment of ARCs. These alternative routes teacher of record, and these programs began to spread across the nation (Johnson, Birkeland, & Peske, 2005; Murnane & Steele, 2007). ARCs gained popularity for a variety of reasons, not only er, but also because many ARCs strived to eliminate some of the barriers (e.g. GPA, SAT, ACT scores, etc.) that many TRCs set in place in order to improve teacher quality (Johnson, Birkeland, & Peske, 2005; Murnane & Steele, 2007). Despite the continuous e fforts of TRCs, they faced rising criticism from both the public and academic sphere, which also led to the increase in ARCs (Imig & Imig, 2008; Kumashiro, 2010; Madigan, 2011 ) Critics of TRCs, such as Madigan ( 2011 ) proclaimed that TRCs act as gatekeeper

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38 pathways were more cost efficient, and there was often more flexibility offered for prospective teacher can didates who were already working in other professions, which supported the effort of decreasing the teacher shortage in America while also increasing the diversity of teachers (Abell Foundation, 2001; NCES, 2018 ; Feistritzer, 1998; Feistritzer, 2001; Haber man, 2004; Johnson, Birkeland, & Peske, 2005; Murnane & Steele, 2007; U.S. Department of Education, 2002; U.S. third of first time pu blic school teachers hired entered the profession through an alternative program other than a college campus ix ). As of 2012, across 48 states American teachers ( NCE S, 2018 ). Because there is such a diversity of quality and quantity of preparation programs offered in the United States, many researchers have recently argued that defining critical features of what ficult an d possibly unrealistic (Kumashir o, 2011; Rosenberg & Sindelar, 2005; Sass, 2011; Zeich n er & Conklin, 2005). Instead, categorizing or sorting the quality and quantity of teacher preparation based on years of experience, completion of certification pathway, degree status, amount of coursework, length of practice teaching, and amount of preparation has proven more useful and productive (Mason Williams & Gagnon, 2016; Rosenberg and Sindelar, 2005). Moreover, as Hogan and Bullock (2012) posit, both TRC [ARCs] will

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39 were participants asked if they attended a TRC o r ARC through a simple binary question, but they were also asked to provide additional information regarding the features of their program as described above to have a clearer understanding of what type of program features have had a relationship, if any, on teacher motivations. These findings could prove useful across a variety of teacher preparation programs. Improving Teacher Diversity and Quality in Florida The burning questions remain how does one attract more, better qualified and diverse teacher can didates, especially those who had not previously considered teaching as a career choice? How does one evaluate whether the goals and aspirations of what originally drew people to the field have changed, and how, if at all, these goals and aspirations have changed over time? In addition, to what extent do either the state of initial or current goals and aspirations affect being, productivity, and commitment to teaching? These questions have caused a variety of initiative s to be launched across the nation, but especially in Florida. For example, the Race to the Top Program has assisted many districts and their schools in increasing and improving their efforts to motivate more, better, and diverse people to choose teaching as a career. Other incentive and support programs available in Florida, especially ones aimed at recruiting minority teachers, are Florida Fund for Minority Teachers, Jacksonville Teacher Residency Program, the M.I.S.T.E.R (Mentoring Instructing Students T oward Effective Role Models), and the Teacher Incentive Fund (TIF) in Orange County Public Schools. These programs often form partnerships with universities and other local stakeholders to provide incentives and support s to attract underrepresented groups from the current teaching force to join the teaching profession, as well as provide a variety of resources, such as financial assistance, mentoring, and guaranteed job placement. Without these resources and support systems, many

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40 Florida teacher candidates may have faced barriers that would have prohibited and discouraged them from entering the field. The Florida Department of Education has also put into place sweeping reforms to increase the teacher quality and diversity of the Florida K 12 students, speci fically as evidenced through their updated statewide performance and assessment matrix of Florida teacher preparation programs. As noted in a report published in 2017, the intent [of these initiatives] is to measure how well the teacher preparation progra m prepares new teachers to work with a diverse population of students in a variety of settings in Florida schools, including economically disadvantaged students, students from major racial and ethnic groups, students with disabilities, and students with li mited English proficiency. (Jacobs, 2017, p. 29) As of 2015, there were 433 by local school districts, 68 by the Florida College System, 189 by the State University System, and 139 by pr However, despite these many changes and incentives, more efforts are still needed to continue to diversify the teaching population and attract effective teachers that meet the specific s students, schools, and school districts. One potential shortfall of the efforts detailed above is that the initial motivational factors that influenced people to become teachers may not have been taken into consideration when developing these initiatives and programs (as evidenced by any reference to the word motivation with the report). Even so, if teacher were well informed with accurate knowledge grounded in theory or empirical research. Understanding Motivation Motivations drive people to do what they do in the way that they do it. Motivational theory is prevalent in the fields of psychology, sociology, business, medicine, career development, and education. Within education, motivational theory has mainly been used

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41 regarding student motivations (Bransford, et al., 2005; Darling Hammond, 2008; Darling Hammond & Bransford, 2005; Pajares, 1992; Shepard et al., 2005; Tomlinson & McTighe, 2006; Wiggins & McTighe, 2005). As Darling students believe about themselves and their abilities, what they care about, and what tasks are any of these theories to inform their practice, research, or policies. While motivation theories abound for student more empirically based research is needed wi th regard to potential and current teacher motivations (Heinz, 2015; Richardson, Karabenick, & Watt, 2014; Watt et al., 2012; Watt & Richardson, 2007; Watt, Richardson, & Smith; 2017). The Need for (More and Better) Motivational Theory in Teacher Educatio n There has been prior research on who chooses the teaching profession and why (Balyer, Richardson & Watt, 2006 2016 ; Salyer, 2003; Watt & Richardson, 2007, 2008). Many researchers advocate that teacher preparation program reform efforts need to focus on teacher motivations to better recruit, educate, and retain high quality teachers (Butler, 2012; 2014; Heniz, 2015; Kaplan, 2014; Krasnoff, 2014 ; Leech & Haug, 2015; Leech H aug, & Nimer 2015 ; Roth, 2014; Sinclair, 2008; Urdan, 2014; Richardson, Karabenick, & Watt 2014; Watt & Ri chardson, 2007; 2008, 2012 ; Yong, 1995). However, as mentioned previously, most of the literature from the late 20th century had not been conduct ed in a systematic way and portrayed a weak methodological, theoretical, and systematic structure (Heinz, 2015; Richardson,

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42 item indicators, raw frequency counts results without the inclusion of the actual survey instrument, which ultimately resulted in inconsisten cies across studies (Watt et al., 2012, p. 792). Conceptually, much of the research exploring why people choose teaching as a career had previously broadly grouped motivations into three main categories: intrinsic, extrinsic, and altruistic (Heinz, 2015, p 263; Watt & Richardson, 2014; Yong, 1995, p. 276). These vague categories limited the understanding, distinction, appreciation, as well as application of effective motivational theory in teacher education (Guzel, 2011; Watt et al., 2012; Watt & Richardso n, 2014). For example, research exploring why people choose teaching as a career has indicated that one of the most common motivations to classified as both altruistic and intr insic across several studies. In addition, many studies only focused on teacher burnout, retention, and self efficacy, without regard to sociological contexts or underlying psychological elements. (Guzel, 2011; Heinz, 2015; OECD, 2005; Lortie, 1975; Kyriac ou & Coulthard, 2000; Richardson & Watt, 2014 2016 ; Watt et al., 2012; Yong, 1995). Consequently, the knowledge and definitions generated from these studies not only weakened the literature base, but it also crippled initiatives that based their efforts o n the results and findings of these studies. To get to the heart of what factors motivate people to become teachers, many researchers sciences can offer to better un p. xiv ). There are some current studies

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43 that ground their research in motivational theory, and the four most established motivational theories a determination Watt & Richardson, 2007, 2008, 2012, 2014; Wigfield & Eccles, 2000). Researchers advocate that these motivational theories, as well as others when used appropriately, can offer key insights into what factors attract the best teacher candidates, how to off er the best preparation and learning experiences, and how to help candidates maintain high motivation as they transfer to professional roles (National Research Council, p. 6). Factors Influencing Teacher Choice: The Development of the FIT Choice Conceptua l Model and Scale In 2006, Dr. Helen M. G. Watt and Dr. Paul W. Richardson of Monash University in Australia brought the use of motivational theory in teacher education to the forefront, specifically with their development of the Factors Influencing Teache rs (FIT) Choice conceptual model and (see Figure 1 1 ) To improve upon the conceptual and theoretical gaps using motivational theory in teacher education research, Watt a nd Richardson endeavored to develop a unified and comprehensible theoretical model for studying teacher career motivations. They drew from several bodies of literature such as motivational theory, teacher education, teaching career choices, self perception s and self efficacy, as well as occupational choice research. Watt and Richardson Expectancy ac ademic and career choices to develop the FIT Choice Conceptual model, and corresponding FIT Choice Scale Both will be explained at length in

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44 social influences and prior teaching and learning experiences, which then affect complementarily designed FIT Choice Scale contains 18 factors to assess the primary motivations of people to choose a career in teaching. Figure 1 1. FIT Choice Conceptual Model. current literature in motivational theory in education res earch, but more importantly, it provides a clear, coherent, and cohesive framework and measurement tool. last decade has been the design of the Factors Influencing Teaching Choice (FIT Choice) scales

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45 Choice framework has been widely used in a range of cultural settings and different samples, such as Austria, China, Croatia, Estonia, Germany, Indonesia, the Netherlands, Norway, the Republic of Ireland, Switzerland, and the United States. Many studies which have used the FIT Choice Scale have reported similar high levels of construct validity and intern al consistency when replicated and used in other schools, settings, or countries with preservice teachers (Akar, 2012; Berger & D'Ascoli, 2012; Brandmo & Nesje, 2017; Fokkens Bruinsma & Canrinus, 2012; Gratatcs, Lpez Gmez, Nocito, and Sastre, 2017; Henn essy & Lynch, 2017; Heinz, Keane, & Foley, Richardson & Watt, 2010 2016 ; Watt & Richardson, 2007; Taimalu, Luik, & Tht, 2017; Watt et al., 2012; Yu & Bieger, 2013) The FIT Choice Scale has been used in a limited number of research studies in the U.S. with regard to preservice teachers (Lin et al., 2012; Watt & Richardson, 2012; Watt et al., Y u & Bieger, 2013; Yu 2011) in service teachers (Leech & Haug, 2015; Leech Haug, & Nimer, 2015; Leech, Haug, Ridgewell, & Ruben, 2018), and high school students (Leech, Haug, & Bianco, 2015). These studies have found that the FIT Choice Scale to become a teacher. These studies typically fall into three main categories: 1) measurement studies that focus on understanding the reliability, validity, and overall fit of the model to various data sets in specific populations 2) comparison studies t hat examine the overall average motivational score and/or using comparisons between/among different groups of preservice and 3) studies that focus on understanding teacher motivations by examining their

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46 above studies align with the first category (Akar, 2012; Berger & D'Ascoli, 2012; Fokkens Bruinsma & Canrinus, 2012; Hennessy & Lynch, 2017; Kilin et al., 2012; Leech & Haug, 2015; Leech, Hau g & Bianco, 2015; Lin et al., 2012; Richardson & Watt, 2010 2016 ; Watt et al., 2012; Yu & Bieger, 2013). A few studies, including Jugo (2012), fall into the latter category where additional factors are incorporated into the FIT Choice model for an expanded viewpoint of their sample. It is in this vein that my study aligns. 7) FIT Choice Scale not only brought about a resurgence of the quantity of motivational theory in teacher education, but more importantly, increased the quality of research, by developing a framework that was conceptually, methodologically, and psychometri cally sound upon which to build and expand future studies. Many other researchers using the FIT Choice Scale coincide with what Watt and Richardson posit. These researchers concur that in order to develop a deeper understanding of how motivational theory can be used to increase the quality and quantity of teachers, it is imperative to examine and track tea understand and explain to what extent these motivation s, beliefs, and influences change over time, as well as make comparisons across different settings and groups of teachers ( Butler, R., 2014 ; Heinz, 2015; Kaplan, 2014; Leech & Haug, 2015; Leech, Haug, & Bianco, 2015; Richardson & Watt, 2007; Richardson, Ka rabenick, & Watt, 2014; Roth, 2014; Watt & Richardson, 2006, 2012). Notwithstanding the resurgence of motivational theory in teacher Choice Scale the use of their model requires further exploration across more and diverse samples, given the necessity to continue to increase the quantity, quality, and diversity of the teaching population locally, nationally and internationally.

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47 Purpose Statement The purpose of my quantitative, retrospective exploratory study was to use survey research methods using the FIT Choice Scale to examine the initial motivations of in service Florida K 12 public school teachers to elect teaching as a career, and to explore the extent to which specific teacher characteristics and teacher prep aration program characteristics had a relationship to particular motivational factors. I endeavored to uncover what influences, beliefs, and values were on average, most important to current Florida K 12 public school teachers in choosing a career in teac hing, categorized into certain typologies (e.g. gender, race, certification) based on their personal characteristics and/or the teacher preparation program in which they participated. Resultantly, the following research questions guided my research study. Research Questions RQ 1 What were the motivations of Florida K 12 public school teachers to choose teaching as a career, as measured by the FIT Choice Scale ? RQ 2 To what extent do teacher characteristics (age, race/ethnicity, gender, native language, pr ior non teaching work experience) and teache r program characteristics (route to certification, prior educational coursework, prior teaching experience, level of education, and length of teacher pre paration program) have a relationship with each motivationa l factor score? Research Design To uncover what motivational factors, on average, contributed to Florida teachers electing teaching as a career, as well as investigate to what extent teacher characteristics and teacher program characteristics had a relati onship to a particular motivational factor, I used survey research methods grounded in both expectancy value theory and a vetted framework the FIT Choice Scale and Survey a measurement tool that has repeatedly reported high validity and reliability of scor es in a variety of contexts (Richardson, Karabenick, & Watt, 2014; Watt et

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48 al., 2012; Watt, Richardson, & Smith, 2017). I also used consistent terminology found throughout the literature base; however, an exploratory retrospective design was chosen becaus e there was little empirically based evidence on which to build this study in this specific context Florida K 12 public school teachers. The e xploratory design examined correlations among various variables and constructs in order to provide thought leaders hip for future initiatives or strategies in teacher education, as well as field of education at large with regard as to how to best recruit, and ultimately prepare and retain teachers in the state of Florida (NSF, 2013, p. 9). These intentions aligned with tions for exploratory studies: knowledge to inform the development, improvement, or evaluation of education programs, po association (or relationship) between two or more variables using the statistical procedure of ; as suc h, I did not attempt to control or manipulate the variables in this study, or the pa My study also was retrospective because I asked participants to reflect upon their past motivations for choosing a career in teaching. To answer t he first research q uestion, descriptive statistics, specifically mean scores and standard deviations of participants 58 Likert scale items (1 7) were used to measure scores and provided data to interpret Florida K motivations To answer the second research question, inferential statistics, specifically simultaneous multiple regression, were used to estimate the association of the independent variables (teacher characteristics and teacher preparation program characte ristics) on the dependent variables

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49 (motivational factors). The data measured in these instruments were collected cleaned, and coded as numbered data for analysis using statistical procedures (Creswell, 2014). Significance This study contributes to the existing literature by exploring the initial factors that motivated Florida teachers to elect teaching as a career using the FIT Choice Scale The motivational factors measured by this instrument produced scores that helped identify the extent to which dif ferent types of teacher characteristics and teacher preparation program characteristics have a relationship to Florida teacher motivations. As Watt and Richardson (2014) found, research generated using the same measurement tool in a variety of contexts bot h enriches and expands the ways in which comparisons can be drawn based not only on motivations, but also the formation of policies concerned with teacher pr ofessional development (p. 9). Given the scope of this study, d ata reported could provide a baseline of information in an area where little empirical research has been reported. As aforementioned, there are only three studies to date that have used the FIT Choice Scale with in service teachers within the U.S., and both the population of interest (a Western state) and variables of interest differed from my study. Even though the nature of my study was exploratory, inform the development, improvement, or evaluation of education programs, policies, or sis, my study contributed to understanding how motivational theory, specifically wit h the FIT Choice Framework, could be used within teacher education research in the state of Florida. By using the FIT Choice Scale within the state of Florida with current K 12 public school teachers, my study has the potential to extend the existing body of research on FIT Choice Scale with

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50 current teachers, particularly in the U.S., a subject only marginally explored in existing literature. My study sheds light on certain factors that were most important to Florida K 12 public school teachers who chose a career in teaching, as well as measured how teacher characteristics and/or teacher program characteristics had a relationship w ith certain motivational factor scores It is in this manner that providing baseline data may provide education and teacher education researchers, methodologists, policy makers, and other stakeholders a firmer basis on which to make informed recommendations and decisions to better recruit, and ultima tely prepare, support, and retain teachers with unique and proportional characteristics to meet the diverse educational However, the u nique attributes of my study were also a double edged sword in that be cause my study is exploratory in nature, it is limited by this distinctiveness, thus requires the need for future research to replicate and expand my findings (which will be discussed later in Chapter 5) In addition, due to its uniqueness, any direct comp arisons with prior studies should be made with caution. Limitations Due to the nature of the design, data collection instrument, and proposed sample population, my study presented a number of limitations. Given the design of this study, the sampling plan w as a potential threat to the validity of my study and limit my ability to generalize my findings to the general Florida K 12 public school teacher population Because I used a convenience sample as opposed to a random sample my sample may not have been rep resentative of the population. However, one way to mitigate some of the threat was to (Kline 2009, p. 68). T he demographics of my sample were, indeed, similar in nature to the K 12 public school teacher population in Florida.

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51 of the study Florida public K 12 schools. Althou gh the teachers received a link to the survey electronically, they received it through their school email address and typically accessed it while they were at their place of employment. Additionally, the time of year I distributed the survey, May, could ha ve affected the response rate, as it was the end of the academic school year. There was the potential that the participants would respond differently if they were to receive this survey in a different setting, timing, or manner (Kline, 2009). There was al so a threat to validity of scores because the FIT Choice survey was originally created as a paper and pencil survey, but due to the scope of this study and the proposed population of all active teachers in the state of Florida (~174,000), a slightly revise d, electronic version of the survey was distributed. Another possible limitation of utilizing an online survey tool could be a lower response rate than an in person, paper and pencil instrument. In this situation, self selection bias became a limitation, a s with any online survey research (Sreejesh, Mohapatra, & Anusree, 2014). Other limitations and subsequent threats to the validity of my study, and the degree to which I could provide sound evidence to support the accurate interpretations I inferred from t he motivational factor scores were due to self selection and voluntary participation in my study ( AERA, APA, & NCME, 2014 ). There could be a difference of responses between the type of people who agree to do surveys/experiments and the type of people who d o not and that all responses were honest and accurate. One other potential validity threat was that there were no external factors that u nduly influenced the responses. Organization of the Dissertation This dissertation includes five chapters, in addition to references. Chapter 1 is the rationale for this study, providing the background and overview of the problem. It also includes a statement of the problem, what we currently know and do not know about the problem, a purpose

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52 statement for the study, and t he research questions driving this dissertation. Chapter 2 provides the conceptual model of the study, a literature review covering motivational theory, motivational theory in education, and a deeper description of the FIT Choice framework. Chapter 3 descr ibes the methods used in the study, the population and variables of interest, and the measurement tool used in this study, the FIT Choice survey. Also included in Chapter 3 are the statistical and analytic procedures used, specifically descriptive statisti cs to compute mean scores from the estimate the relationship between teacher and teacher program characteristics and particular motivational factor scores. Chapter 4 provides the results from the data analysis. Finally, Chapter 5 consists of a discussion of my findings relative to previous studies, and implications of the results for various audience.

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53 CHAPTER 2 LITERATURE REVIEW The purpose of my quantitative, retrospective exploratory study was to use survey research methods using the FIT Choice Scale to examine the initial motivations of in service Florida K 12 public school teachers to elect teaching as a career, and to explore the extent to which specific teacher characteristics and teache r preparation program characteristics had a relationship to particular motivational factors. I endeavored to uncover what influences, beliefs, and values were on average, most important to current Florida K 12 public school teachers in choosing a career i n teaching, categorized into certain typologies (e.g. gender, race, certification) based on their personal characteristics and/or the teacher preparation program in which they participated. The review of the literature in this chapter discusses the need to use motivational theory to support these efforts, and the types of motivational theories that are currently used in education research. Evidence from the literature supported the use of the theoretical model for this study Watt and Rich Choice framework a nd how it best aligned with the goal of measuring and interpreting the initial motivational factors for people to choose teaching as a career. Motivational Theory Motivations drive people to do what they do in the way that they do it. Motivatio nal theory is prevalent in the fields of psychology, sociology, business, medicine, career development, and education. or a combination of any of these theories to inform their practice, research, or policies. There are several theories that comprise the greater subject of motivational theory, but the genesis for the motivational theory utilized in this study lies within the Expectancy Theory of motivation,

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54 make conscious decisions when presented with choices, which will maximize their own pleasure and minimize their pain (Vroom, 1964) Motivational Theory in Education While motivational theory has been used widely in education, the focus has been 2005; Bransford, Darling Hammond, & LePage 2005; Darling Hammond, 2008; Shepard et al., 2005; Tomlinson & McTighe, 2006). While there has been systematic research, investment, and continued interest pertaining to motivation, engagement, and learning of students, this is not necessarily th e case f or teachers even though teachers are life long learners, too. Despite century ago that there was a a know which attributes not only to evoke, but also to either reinforce or alte r (p. 37), few candidates into the teaching profession, [has t eacher motivation] attracted a more systemic over the last ten years, that are more conceptually and methodologically sound, much of which has been guided by Wa Choice framework (Butler, 2017; Heinz, Motivational Theory in Teacher Education One aspect of the efforts to recruit, prepare, and retain more and better quality teachers that require quality

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55 teachers (i.e., those who are well prepared, experienced, and accomplished) into K 12 educational settings, research suggests that schools must match their recruitment and re tention efforts to the characteristics and motivations of the teachers and teaching candidates they hope to Krasnoff, 2014 p. 12). This sentiment can be replicated into the teacher education sphere as well, as teacher preparation programs must a lso match their efforts to the motivations of prospective teachers (Heinz, 2015; Krasnoff, 2014 ; Leech, 2015; Richardson, Karabenick, and Watt, 2014; Sinclair, 2008; Watt & Richardson, 2007; 2012 2016 ; Yong, 1995). As Heinz (2015) states, While academic skills are important factors contributing to teacher effectiveness, quality education cannot be achieved without teachers who are motivated, enthusiastic, and truly committed to their students In this context, more evidence based research is needed to determine and consistently measure the factors that motivate and influence people to elect teaching as a career, what goals and beliefs they value and what backgrounds, dispositions, and characteristics they possess (Watt & Richardson, 2005, p. 488). The research and subsequent knowledge generated from the admi nistrators need to understand how motivation and personality influence student decisions sion and desire to pursue and maintain a career in that field. Recent studies over the last decade have connected the relationship betw motivations towards electing his or her career

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56 The Need for (More and Better) Motivational Theory in Teacher Education Until recently, motivational literature and teacher education literature have operated in isol know about career choice across a range of careers had not influenced the research concerning he late 20th century on teacher motivations focused on teacher burnout, retention, and self efficacy (Guzel, 2011; Watt et al., 2012; Watt & Richardson, 2014; Yong, 1995). While there are studies in teacher education literature that have explored why peopl e have chosen to become teachers (Balyer, & zcan, Yong, 1995), the majority of these studies are not born out of systematic research, and there are a This is for several reasons: 1) there has been inconsistent terminology in the literature, making it difficult to generalize or compare study findings, 2) until recently, ther e has been little use of motivational theory to guide these studies and 3) more longitudinal studies are needed to better understand initial motivations, and how they change over time (Watt et al., 2012; Watt & Richardson, 2007). Prior research studies use d more rudimentary tools and techniques and failed to fully report the methods of the study, leading to inconsistencies and confusion in this f ield. (Watt et al., 2012 ). Again, combining all motivations into poorly defined, inconsistently used, and vague c ategories of intrinsic, extrinsic, and altruistic (Heinz, 2015; Watt & Richardson, 2014; Yong, 1995 ) caused further confusion and inconsistencies across studies (Guzel, 2011; Watt et al., 2012; Watt & Richardson, 2014). Furthermore, while it has long been the frequently interchanged classifications of this factor as altruistic and intrinsic has continued

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57 to interfere with the growth and r ecognition of motivational theory amongst teachers, in essence blocking potentially beneficial initiatives before they could even begin. Over the last two decades, there has been an increase in empirically based research that examines why students choose t eaching as a career (Guzel, 2011; Watt et al., 2012; Watt & Richardson, 2014). The four theories listed below self efficacy, achievement goal theory (AGT), self determination theory (SDT), and expectancy goal theory (EVT) are the most prevalent. These fram volume, Teacher Motivation: Theory and Practice as well as the 2017 expansion, Global Perspectives on Teacher Motivation by Watt, Richardson, and Smith, with over 60 authors contribu ting to the rapidly expanding research utilizing the FIT Choice Scale. Over twenty essed by their xxi ). These authors present new motivates and sustains healthy, committed, and effective teac Watt; 2014, p. xiv ), but also offer a better understanding of teacher quality and career development, and how to support those goals in teacher education. Until the gaps that currently exist between understanding what motiv ates people to choose teaching as a career, how different factors motivate different people to the field, and which pathways are preferred by whom, are filled, recruitment efforts will continue to maintain aching continues to attract only a narrow slice of graduates, the status of the profession will remain what it is today below that of other professions that require a similar level of intellect, resolve, creativity, and prepar 541).

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58 This shortfal l is where motivational theory can have a significant impact on guiding educational stakeholders to seek the best candidates for their particular programs and/or if programmatic changes need to be made. However, the unique attributes of my study are also a double edged sword in that because my study is exploratory in nature, it is limited by this distinctiveness, thus future research is required to replicate and expand my findings. In addition, due to its uniqueness, any direct comparisons with prior studie s should be made with caution. The Four Most Established Motivational Theories Within motivational theory, there are many specific theories, and, to date, four of the R., 7; 2012; Wigfield & Eccles, 2000). Researchers advocate that these motivational theories, as well as others when used appropriately, can offer key insights into what factors attract the best candidates, how to offer the best preparation and learning experi maintain high motivation as they transfer to a professional role (National Research Council, p. 6) Self E fficacy Self the most heavily researched areas of teacher motivation (Urdan, 2014 ). Research on self efficacy can goals is encouraged, developed, fostered, and/or mainta efficacy is environments conducive to development of cognitive skills rests heavily on the talents and self efficacy of teacher efficacy are

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59 more likely to be able to motivate their own students and increase critical thinking skills, while teachers with lower levels of self efficacy have a tendency to have a more cus todial and punitive orientation (Bandura, 1994). Achievement Goal Theory engaging in action, the patterns of those actions, and the systems of meaning that frame th ose actions (Ka plan, 2014 ). AGT has been used frequently when studying K 12 student motivations Butler, R., 2014 p. 21) AGT has set their goals for achievement/success, and what action steps they take to reach their goals (Watt & Richardson, 200 7 ). AGT can provide insights into how current teachers can develop coping strategies when faced with the challenges and difficulties of teaching. Furthermore, it provides specific job tasks ( Butler, R., 2014 ). Self Determination Theory Self (Kaplan, 2014, p. 53). According to SDT, when people feel that their needs are satisfied, their subsequent actions feel more autonomous, adaptive, and oriented for personal growth people feel they are in control of their actions and lives as opposed to external circumstances or acts of coercion. SDT has shed light on to how environments that support autonomy are likely to positively motivate teachers, which in turn can lead to positive outlooks on their roles and

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60 responsibilities as teachers. Conversely, environments that lack or inhibit autonomy can quent actions (Roth, 2014 ). Expectancy Value Theory Expectancy and posits that people believe their performance will be followe d by success or failure, and then investment, and persistence in itself for use with teacher candidates to measure their initial motivations for entering the field but can also be used over time to track the changes, if any, in teacher motivations. Eccles an d EVT model is one of the most widely used for determining K especially with regard to math participation, and has more rece ntly been applied to specific career choices, in cluding teaching as a career EVT choices and behaviours [ sic ] & Richardson, 2008, p. 410 ). Their conceptual framework encompasses three higher order constructs and subseq Choice model (p. 171). Why EVT? A Summary of Above Theories SDT, along with AGT and Self Efficacy frameworks, can offer great insights into how interactions with students, the effort and time they devote to their role as a teacher, as well as their overall self perception as to how they become confident and satisfied with their work. These theoretical frameworks can help

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61 improve efforts to retain teachers once they are in the field, as well as support the development of teacher leaders within the field. As Watt and Richardson (2014) proclaim motivations matter, because if teachers are not able to realize their motivations in particular sc ( p. 194). However, these frameworks are limited when the initial motivations for entering into teaching sional development and professional The process of becoming a teacher begins prior to their experiences in a teacher preparation pathway, and there is a gap in the lite rature regarding the quality, consistency, and coherency of motivational research in teacher preparation program development and reform (Watt & Richardson, 2014). EVT aims to explore the initial motivations before completing a task, or, specifically in tea career. Therefore, EVT, or other frameworks that include components of EVT, would be the s (2007) FIT Choice framework, which expanded upon the EVT (Eccles et al., 1983; Wigfield & Eccles, 2000) framework as a basis for their model. Factors Influencing Teacher Choice: The Development of the FIT Choice Conceptual Model and Scale Watt and Richa rdson (2007) aspired to improve upon the conceptual and theoretical gaps c areer in teaching. In reflecting back to what originally motivated them to create the FIT Choice Scale, given the limitations of the field, Watt et al for becoming a teacher is a scale that encompasses the arr ay of motivations, which taps into the

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62 underlying psychological processes that can be used to study different groups of people from themes of several bodies of li terature: teacher education, teaching career choices, self perceptions and ability beliefs, as well as broad career choice research to develop the FIT Choice Theoretical Framework. In their initial study, Watt and Richardson (2006, 2007) conducted their re search across two independent large scale samples in Australia. The participants in this preliminary study were two cohorts of preservice teachers one graduate and one undergraduate at two different Universities in two Australian states in 2002 and 2003. T hey collected their data in two Phases: Phase 1 took place at the beginning of the academic year, and Phase 2 occurred at the end of the academic term. The surveys were administered in person via a paper and pencil format. Once the data were collected, Wa tt and Richardson (2007) first completed exploratory factor analysis (EFA), followed by confirmatory factor analysis (CFA). Exploratory factor analysis is a more inductive approach, where one first analyzes items, estimates what the items are measuring, an d then names/categorizes them in a way that matches theory or previous research. Confirmatory factor analysis is a more deductive approach, where one uses relevant theory and research to decide in advance what the factors or constructs are, how they will b e interpret the accuracy of the predictions (Keith, 2015). Watt and Richardson (2007) completed EFA across motivation, belief, and decision items, on the full set of factors with the data from und ergraduate cohort of University 1. Next, they completed the same procedure with the data collected from the graduate cohort of University 1. They staged their analysis in this way so as to avoid over capitalizing on sample

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63 characteristics. In other words, across the combined cohorts at University 1 ( N =488) on the full set of first order factors established by the antecedent EFAs. Through this third analysis, they were able to establish both convergent and divergent construct validity across the set of motivational factors (whether the factors were similar enough to converge to form a factor or whether they diverged or differed enough to form separate factors) (Watt & Richardson, 2007). Watt and Richardson (2007) then used this information to conduct a nested CFA with the two combined cohorts (undergraduate and graduate) at University 2 ( N =652), to determine which items could serve as indicators for respective first order constructs (which particular items could measure a factor) while simultaneously determining which first order constructs could be subsumed as indicators for higher order constructs (which fac tors and their subsumed items could be converged into a higher order factor). Stated plainly, the statistics generated from the CFA established whether or not the model adequately explained the data, as well as to what extent the predictions were accurate (Keith, 2015, p. 333). Scores indicated high construct validity, with factor loadings (LX or LY) ranging from .50 to .95 at the first order level, and .52 to .93 at the higher order level. The scale also displayed acceptable internal consistency and reliab ties ranging between .62 and .92 developing both the framework and subsequent scale was not simply self serving; instead it was in hopes of Over the last decade, their research has expanded into the FIT Choice project

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64 (www .fitchoice.org), and the continuity of the use of their framework and instrument have helped to address some of the aforementioned limitations in the field. The synthesis of their model not only supports current literature in motivational theory in educati on research, but, and maybe more importantly, it provides a clearer, more coherent, and cohesive framework. As a motivations research in the last decade has be en the design of the Factors Influencing Teaching Choice (FIT in over a dozen studies internationally (the details of these studies will be discussed further after the descript ion of the model). For clarity and coherence, Watt and Richardson (2007) renamed and restructured the ( Eccles et al., 1983; Wigfield & Eccles, 2000) EVT framework (as described above) t o 1) task perception 2) self perception (formally self ), and 3) values respectively, as well as included a fourth construct, fallback career These four constructs represent the overarching category of proximal influences. Watt and Richardson (2007) furt her developed their model to include antecedent influences that preceded the proximal influences of the eventual outcome to choose teaching as a career. Listed below are Choice conceptual model with both a narrative description and supporting evidence from the literature. The studies provided under each motivational factor are both FIT Choice and non FIT Choice studies. The non FIT Human Development Index (HDI) score, indicating similar level of development. However, as noted earlier, there have been inconsistent uses of terminology in the literature, and there may be some overlap and/or discrepancies in how the factors are categoriz ed. For example, in Watt and

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65 children has been identified as one of the central motivations for becoming a teacher (Balyer & been categorized as both intrinsic and altruistic (Watt & Richardson, 2014, p. 3). Antecedent Socializ ation I nfluences A ntecedent socialization influences are happenings in daily life that help guide the direction of a career path when the time comes to make a decision. Three such antecedent factors are social dissuasion, prior teaching and learning experi ences and social influences on a career dec ision Social D issuasio n Historically, social dissuasion has profoundly shaped the field of teaching, especially regarding gender roles because teaching is often perceived as a job for women rather than men. As s uch, males might be discouraged from joining the field. In addition to their own beliefs, prospective teachers might be discouraged from becoming teachers by their family, friends, communities in which they live, and even the media (Hammerness et al., 2005 p. 367; Howard & Milner, 2014; Reynolds, 2016). Moreover, highly successful students are often dissuaded from T n, and as with other occupations stereotypically designated primarily for women (e.g. clerical work, nursing, social work, etc.), teachers are usually regarded with less prestige (Herbst, 1989; Ingersoll, 2007; Nash, 2005; Tyack, 1974). As Ingersoll (2007) professions, teaching has been considered a less attractive and less desirable line of work. This

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66 Add itionally, opportunities for advancement within the field for females are typically few and far between, as males continue to dominate the administrative roles. In light of this, it has been commonplace for peers and family members to attempt to dissuade i ndividuals from pursuing teaching as a career choice. However, the FIT Choice scores describing the level of social 3 ) participants returning the highest mean score of 4.55 (2013). On the other end o f the spectrum, the Swiss participants responded with the lowest overall perception of this factor of 2.52 (Berger & D'Ascoli, 2012). Prior Teaching and Learning E xperiences ed by their prior teaching or learning experiences (Hammerness et al., 2005; Howard & Milner, 2014; Reynolds, 2016). Many teachers had positive learning experiences as students and chose to become a teacher based on these experiences, or because they wish to emulate a favorite teacher, make an impact on a future generation, or aim to specifically aid an underrepresented group. Many underrepresented students may experience a level of disengagement in their learning experiences. While the teaching population demographics have remained similar over the past several decades, the diversity of students has risen, and many students may feel a disconnect between themselves and the dominant culture of their teachers. Students who are not part of the dominant culture may often have negative learning experiences in school, become disengaged (Gallagher, 1994; Tai, Liu, Maltese, & Fan, 2006) and could feel ostracized as experiences result in detrimental effects on students of color as a whole, but also play a role in experience s as students, they are unlikely to choose professions in school set tings, unless other factors and values (e.g. monetary incentives, increase in social status, self efficacy, enhance

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67 social equity) outweigh those past experiences. One such result is that students who feel disconnected from the curriculum often drop out of school, reducing the number of possible candidates who even go to college (Daughtry, 1989; Hrabowski & Sanders, 2015). Another issue is that because of the inequality of education, students of color are at a much greater risk of not meeting the high colle ge entrance standards required for admission into many colleges and universities (Hrabowski & Sanders, 2015; Rettig & Khodavandi, 1998). This then reduces the number of possible candidates to enter college and to choose teaching as a career. In contrast to the first motivational factor within this section, prior teaching and learning experiences were reported to have a higher mean score than social influences in the FIT Choice studies. The strongest reported relationship between prior teaching and learning experiences and a decision to choose teaching as a career was reported by three U.S. based samples with preservice teachers. The studies conducted by Lin et al. (2012), Watt et al (2012), and Yu and Bieger (2013) reported means of 5.73, 5.80, and 5.93, re spectively, to display the highest means amongst the studies. On the other end of the scale, the Dutch participants provided the lowest mean score of 3.83. Social I nfluences ambitions, and knowl edge as he/she endeavor s to elect a path to pursue a career. In addition to the internal factors at play, teaching profession as well as other professions. . t hey choose it under the influence of others that the second most important extrinsic reason for choosing teaching as a career was the some were encouraged by their parents as either one or both were teachers, others were inspired by their previous teachers, and a few were forced by their parents

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68 ay begin to connect to the idea that teaching is a female occupation, along with nursing, clerical work, and do mestic service jobs (Apple, 2013 ). While it may not always be the case, some females may be encouraged more than males to become teachers. In exa mining the seventeen samples of quantitative FIT Choice studies available, social influences produced relatively low mean scores, representing that the outside factors, as mentioned above, did not play heavily on their decision to pursue teaching as a care er. Proximal Influences teacher, but some are more proximal to a personal values. This second set of motivational factors g uiding the choice to become a teacher examine factors closer, or more proximal, to the individuals, and also take into account cultural orientations and values (Heinz, 2015). Task P erceptions The first set of proximal influences described in Watt and Rich restructured task perceptions into two specific groups, or higher order constructs : task demand and task return Task demand is measured by expertise and difficulty Task return is measured by social status and salary. These construct demands and rewards of teaching. Researchers have suggested people are extrinsically motivated to become teachers, and are driven by factors such as salary and work conditions (Kyriacou & Coulthard, 2000 ; Lai, Chan, Ko, & So, 2005). This tradeoff can carry considerable weight regarding their choice to enter the teaching profession.

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69 Task d emand Watt and Richardson (2007) developed the two higher order components, task demand and task return, to determine t Do you think teaching requires high level of expert knowledge? ) and difficulty (e.g. Do you think teachers have a heavy workload? ). Task return also contains two factors: salary (e.g. Do you think teachers earn a good salary? ) and social status (e.g. Do you think teaching is a well respected career? perceived expertise and knowledge required (high or low) to teach, as well as the difficulty of performing the task. Expertise. The perceive d level of expertise required to teach varies drastically across prestige, while the liberal arts and sciences with less. Additionally, teachers in higher educa tion are typically perceived as requiring more expertise, followed by secondary, middle, and primary grade teachers. Moreover, the genesis of the discrepancy in what area is the most respected can be traced back to universities and colleges. There has alwa problematic issues of perceived expertise required to teach effectively is the perceived ease of access into teacher education progr ams at universities, as well as the availability of numerous routes and pathways into education (Ingersoll, 2007, p. 10). Most prospective teachers from highly developed nations such as Switzerland, Germany, and the U.S. reported that teaching was a profes sion which required a vast amount of expertise with means (M) =5.86, 5.76, 5.55 (Berger & D'Ascoli, 2012; Knig & Rothland, 2012; Leech & Haug, 2015). The Chinese participants of

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70 actor score of just 2.77, a full three points lower than their Swiss counterparts (2012). Difficulty. nd these perceptions vary widely across the globe (Ingersoll, 2007; Lin, 2012; Watt & Richardson, 2007) For society has ebbed and flowed from rudimentary ba by protectors of the global economy (Bailyn, 1960; Kaestle, 1983; Mann, 1841; Nash 2005; Spring, 2014). As the roles and respo nsibilities of teachers evolved, so too did the professionalization of the occupation, especially regarding social status, gender roles, compensation, certification and education requirements, and collective goals of the professorate (Darling Hammond 2010, 2015; Ingersoll, 2007; Spring, 2014). supported by the results of many of the FIT Choice scale studies that have taken place in the last decade. Eight samples of participants reported motivational factors mean scores over 6.0, and the top ten hi ghest reported that views of difficulty and level of demand stemmed from only Australian or U.S. samples (Leech & Haug, 2015; Lin et al., 2012; Richardson & Watt, 2006 2010 2016 ; Watt et al., 2012; Yu & Bieger, 2013). Once again, the Chinese sample repor ted much lower mean scores, with a mean of 3.41, representing that the Chinese preservice teachers studied did not view the teaching profession as a difficult career (Lin et al., 2012).

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71 Task r eturn Task return refers to the salary, social status, and othe r compensation for becoming a teacher. Currently, American teachers are charged with the daunting task of preparing the next generation of students to restore the economy of the United States to compete in the 21st Century global market, while typically wo rking long hours with little monetary compensation, low social status, and limited autonomy. Social status. Teaching in the United States has traditionally been a profession of economically lower or middle classes (Balyer & zcan, 2014; Banks, 1995; Durcha rme & Agne, 1989; Ladson Billings, 2005; Sleeter, 2001; Villegas, 1993 ; Zeichner, 2003b ). For decades especially since the rise of alternative routes to certification, many have not consider teaching to be not necessary to have a background in education to become a successful teacher, as long he/she possessed exceptional subject knowledge ( Kopp 2010). Recently, the teaching profession in the United States has become more complex and demanding, yet by and la rge teachers are still not afforded high social status or salary, as discussed above, commensurate with education and experience. In some cases, stripped of their autonomy, while simultaneously having more responsibility and accountability added to their jobs. Once again, the Chinese participants responded with a low mean for this motivational factor of 3.13 (Lin et al., 2012). This time however, U.S. current in service teachers reflected the lowest overall mean score, returning a mere 3.09 average (Leech & Haug, 2015). Salary. Historically, U.S. teachers have typically received lower salaries compared to other professionals who attain similar levels of educati on (Carter, 1989; Lin, et al., 2012). Carter (1989) claims that up until the mid attract qualified teachers despite the low salaries offered because they made the use of the

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72 services of educated wh ite women and educated black men and women whose alternative that the only way to continue to attract and retain well qualified teachers was to increase teacher s alaries (Carter, 1989, p. 60). than other professions. For example, in Singapore, in order to attract the most qualified candidates, teacher candidates are pro vided with m onthly stipends while still in school, and starting salaries are adjusted based on other occupational starting salaries with comparable levels of education (OECD, 2011 ). In the U.S., there have been some national and state programs developed to provide mor e scholarships and forgivable loans in order to motivate more and better qualified people to elect teaching as a care er (Darling Hammond, 2010 ). In most developed countries, social status and salary are often correlated. However, in the FIT Choice study co mparing across multiple nations -Australia, U.S., Germany and Norway -German among these four countries ( M = 4.4), with the U.S. average being over a full point lower ( M = 3.0), while perceived social status among German participants was rated lowest among mean scores ( M = M = 4.2) (2012). Similar results to the German ones were reported in the Swiss study (Berger & D'Ascoli, 2012) Self P erception s The second set of proximal influences was renamed from self to self perceptions and measured by self perception s of teaching ability Many prospective teachers perceive they have a number of strengths they can bring to the classroom. Some teachers state that they are confident in their abilities due to their prior experiences with teaching or training and/or want to share their

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73 love of a subject with others (Salyer, 2003). While some people became motivated to teach later 1995, p. 7). However, as mentioned earlier, there are discrepancies in the findings: Yong (1995) population was preservice teachers enrolled in year 1, 2, and 3 of a primary education program in Brunei Darussalam. Interestingly in the four studies using the FIT Choice survey to perceptions mean scores all occurred in the U.S. in each study ( M 6.09, 6.06, 5.90, 5.83) (Leech & Haug, 2015; Lin et al., across the board perceptions of themselves, as the United States has been shown to have above average levels of self confidence. In fact, The Economist rld 's most self 2008). Values The third set of proximal influences was restructured from the broad theoretical construct of value into three value constructs: intrinsic career value personal utility value, and social utility val ue There are two higher order constructs within proximal influences personal utility value and social utility value under which are several specific motivational factors. Seven factors are combined to create the two higher order factors measuring personal utility value and social utility value Personal utility value is measured by job security time for family and job transferability Social utility value is measured by shape future of children/adolescents enhance social equity make social contribution s and work with children/adolescents Intrinsic career value may have chosen to enter the teaching profession based on the perception that the occupation

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74 aligns with their personal values. Seventeen samples of the FIT Choice scale being utilized found that the intrinsic value teachers place on their profession, due to the alignment with their personal beliefs, rated highly with the range of means from 5 to over 6. The outlier in this situation was preservice teachers in China, who rated their intrinsic value at just 4.1. Of interest, of the intrinsic value of a teaching caree r scored an average of 2.7. Personal utility value Watt and Richardson (2007) developed the higher order component personal utility value, or the reasons that relate to the extent one considers a task to be important or essential to reach personal goals, s uch as quality of life (p. 172). They termed these constructs as: job security (e.g. Teaching will offer a steady career path ), time for family (e.g. Teaching hours will fit the responsibilities of having a family ), and job transferability (e.g. A tea ching qualification is recognized everywhere ). Job security. For some prospective teachers, teaching may offer more job security than other professions, and job availability prospects are often a major motivational factor in choosing teaching as a career (Salyer, 2003). Yong (1995) also reported job security, regular income, and benefits motivated participants to elect teaching as a career (p. 227). Due to teacher shortages in many geographies as well as high teacher turnover (especially in hard to staff s chools), teachers are usually in high demand (Kelly, 2018 ). Time for family. Some believe teaching is more conducive to their intended family lifestyle, especially if they have, or want to have, children of their own (Darling Hammond & Cobb, 1996; Lortie, 1975). Others decided to choose teaching because they would get longer holiday and vacation time, and liked the perceived low time/daily hour commitment (Kyriacou & Coulthard, 2000, p. 123; Yong, 2015). However, teaching hours vary from country to country.

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75 teachers is 38.3; however, Japanese teachers work an average of about 53.9 hours per week (OECD, 2018 ). Conversely, in Brunei Darussalam, the time commitment to teach is considered a benefit, as many teachers only work half a day, five days a week, for about 200 days out of the year (Yong, 1995, p. 277). Within the FIT Choice surveys which recorded mean scores of time for family, there was a substantial range of means reac hing up to 4.56 5.4 for several European studies of preservice et al. (2012). One item that stood out was that the only study on in service teachers reported by far the lowest mean s core as it related to t ime for family at M 2.82 (Leech & Haug, 2015). Job transferability. Finally, in the majority of the world, teaching is recognized of the country, in just about anywhere Cornell University, 2011). Even though certification requirements may vary from country to country (Ingersoll, 2007; Watt & Richardson, 2007) and state to state, there are a variety of rout es available to obtain certification. In the United States, many states participate in reciprocity and accept teaching qualifications from other places (FLDOE, 2017). Therefore, this flexibility offers job security even for families who move frequently (e g. military families) (Kelly, 2018 ). Accordingly, the U.S. returned some of the highest mean scores for job transferability with averages of 4.37, 4.1 which were behind only a Turkish study which returned a mean of 5.11. Once again, in service teachers tes ted within the U.S. returned the lowest mean of 3.08. Social utility value Watt and Richardson (2007) developed the higher order factor, social utility value, as representing a strong desire to give back to society in meaningful ways (p. 173). The four fac tors within social utility are: make social contributions (e.g. Teaching will allow me to provide a

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76 service to society ), shape child and adolescent values (e.g. Teaching will allow me to shape child and adolescent values ) enhance social equity (e.g. T eaching will allow me to benefit the socially disadvantaged ), and work with children/adolescents (e.g. I like working with children and adolescents ). Shape future of children/adolescents. you open up new worlds to your students and provid e them with a gateway to careers the physical sciences, engineering, medicine and technology You really do make a difference ( Cornell University, 2011). Some people choose teaching because they fe el compelled to help shape the lives of future generations of students (Kelly, 2018 ; Kyriacou & Coulthard, 2000 ) and others feel they have the opportunity to benefit the socially disadvantaged. Once again, this motivational factor reported high mean scores across nearly all studies of teachers, ranging from M 4.56 to M 6.31 (Fokkens Bruinsma & Canr inus, 2012; Yu & Bieger; 2013). Enhance social equity. Manuel and Hughes (2006) reported that some preservice teachers wanted to become teachers so they could giv e back to their communities, as well as claimed similar results, and altruistic motivations dominated the justifications for becoming a teacher, especially for fem many commonalities as to why students from different subject areas wanted to become teachers, and the most common were reasons linked to helping others and self realization. Continuing th e theme of high social utility value, enhancing social equity was also a strong motivational factor in participants electing to pursue teaching as a career. With mean scores ranging above 5.6

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77 ty aligned with o ther factors within this group. Make social contributions. As shown in the literature, social utility value is similar to altruism (Watt & Richardson, 2012). Altruism is defined as behavior that is not beneficial or may even be harmful to oneself, but benefits others (Merriam Webster https://www.merriam webster.com/dictionary/altruism). Salyer (2003) stated that some of the motivations and reasons for prospective teachers who choose an alternative route are altruistic in nature, which is si milar to those cited by prospective teachers who choose a traditional route. Many people choose to become teachers because they believe they can help students succeed and make a contribution to society (Salyer, 2003). Making social contributions returned s ome of the highest means from top to bottom, including four studies reporting means over 6.0 (Akar, 2012; Kilin et al., 2012; Lin et al., 2012; Yu & Bieger, 2013). Meanwhile, even the lower reported means ( M 4.70, 4.73) were still reasonably high when com pared to mean scores from other factors (Fokkens Bruinsma & Canrinus, 2012; Watt et al., 2012). Work with children/adolescents. As previously stated, working with children and adolescents is assumed across the education landscape as perhaps the greatest mo tivational factor 2005; Salyer, 2003; Yong, 1995). The FIT Choice studies within this body of literature further validate this viewpoint as the working with children/a dolescents factor provided one of the Yu & Bieger, 2013). While the studies listed above report social utility or altruistic motivations as dominant determ inants for prospective teachers, other studies do not support such claims. For example,

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78 Yong (1995) reported that altruistic factors, such as working with children, contributing to society/country, and imparting knowledge were the least prominent (p. 278). Salyer (2003) also stated that some of the motivations of prospective teachers are altruistic in nature, regardless of what type of certification or preparation pathway was chosen. Fallback Career As mentioned above, in addition to the three aforementione d constructs of task perceptions, self perception s, and values Watt and Richardson (2007) added fallback career as a proximal influence. Studies have suggested that some people who choose teaching as a career had not originally intended to do so, or were unsure of their professional capabilities. For these teachers, they may or may not have been accepted into their first choice career, major, or university, and/or they were unsure as to what career they truly wanted. For example, Yong (1995) reported the m from entering another field or were unable to attain a higher level of education (p. 276). I n the reported means scores in the FIT Choice studies, the motivational factor of fallback career was one of the lowest rated motivations for entering the workforce across numerous studies (Akar, 2012; Berger & D'Ascoli, 2012; Fokkens Bruinsma & Canrinus, 2012; Hennessy & Lynch, 2017; Jugovi et al., 2012; Kilin et al., 2012; K nig & Rothland, 2012; Leech & Haug, 2015; Lin et al., 2012; Richardson & Watt, 2010 2016 ; Watt et al., 2012; Yu & Bieger, 2013). In other words, it appears that teaching was not a fallback career for the majority of participants in previous studies. Outcome: Choice of Teaching Career The final component of the FIT Choice model is the outcome of choice of teaching career Watt and Richardson (2007) created factors within their fra mework measuring the overall

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79 satisfaction with the choice of a teaching career career choice satisfaction Manuel and Hughes (2006) reported the participants in their study were satisfied with teaching, as it met their goals d purpose; a desire to sustain an engagement with their chosen subject(s); and the opportunity to work with young people as part of the broader social project of preservice teachers, and while these prospective teachers often reported they were highly satisfied with their decision, other studies have suggested that once they enter the field full time, their satisfaction decreases. Between 2008 and 2012, job satisf action among teachers declined from 62% of teachers reporting satisfaction, to only 39% (Markow Macia, & Lee, 2013 p. 45 ). Amongst the FIT Choice studies, the responses to career choice satisfaction with preservice or in service teachers were positive ov erall. In a possibly concerning result, the U.S. high school students surveyed responded much more negatively with a mean score of perceived satisfaction with a teaching career of just 2.93 (Leech, Haug, & Bianco, 2015). This negative outlook of teaching as a satisfying career choice for the next generation of working professionals does not bode well for the future of the teaching profession. In reviewing the FIT Choice scale studies from around the globe, one takea way was the juxtaposition between many Western nations and the sample s reported from China. The constant low scores of the Chinese sample in regards to difficulty, required expertise, and social status have been attributed to the collectivist nature of Chi nese society as a whole, and teacher centralized context where they must conform to defined standards in curricula, teaching, Lin et al., 2012, p. 231). Unsurprisingly, the Chinese participants

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80 again returned the lowest career choice satisfaction mean score amongst preservice or in service teachers with a mean of 4.54 (Lin et al., 2012). One additional item of which to be cogniz ant, especially when reviewing the responses of in service teachers, is choice supportive bias (Mather & Johnson, 2000). This bias is a psychological phenomenon in which individuals will look more favorably upon the option they selected. When exploring the in service teachers, as researched by Leech and Haug (2015), regarding the more positive factors such as career choice satisfaction, level of ability involved, and level of expertise required in teaching, the mean scores continually appeared at the upper end of the spectrum. Similarly, when confronted with negative sentiment factors such as salary, social status, and time for family, their scores then became lower than most of those of their preservice counterparts (Leech & Haug, 2015), which could be indi cative that choice supportive bias is taking place. The FIT Choice Survey: Putting Theory to Use There have been over a dozen research studies encompassing seventeen samples using Watt and Richardson's FIT Choice scale (Akar, 2012; Berger & D'Ascoli, 2012; Fokkens Knig & Rothland, 2012; Leech & Haug, 2015; Lin et al., 2012; Richardson & Watt, 2010 2016 ; Watt & Richardson, 2007; Watt et al., 2012; Yu & Bieger, 201 3). This framework has been widely used in a range of cultural settings and different samples, and results from the FIT Choice surveys have reported high validity and reliability scores with several surveys of preservice teachers in Australia. The FIT Choi ce scale has also been used in other countries, such as China and the United States (Lin et al., 2012); Norway, Germany, Australia, and the (Fokkens Bruinsma & Ca nrinus, 2012). The FIT Choice scale has been used in research with

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81 preservice teachers in the United States (Leech & Haug, 2015; Leech, Haug, & Bianco, 2015; Lin et al., 2012; Watt et al., 2012; Watt & Richardson, 2007, 2008; Yu 2011), but on only one occ asion with in service teachers (Leech & Haug, 2015). These studies fall into two main categories: 1) studies that focus on understanding teacher preservice teachers and 2) studies that focus on un the first category (Akar, 2012; Berger & D'Ascoli, 2012; Fokkens Bruinsma & Ca nrinus, 2012; Hennessy & Lynch, 2017; Kilin et al., 2012; Leech & Haug, 2015; Leech, Haug & Bianco, 2015; Lin et al., 2012; Richardson & Watt, 2010; Watt et al., 2012; Yu & Bieger, 2013). A few studies, where additional factors are incorporated into the FIT Choice model for an expanded viewpoint of their particular sample. It is in this vein where my study will align More specifically, this study will explore what initial factors motivated current Florida K 12 public school teachers to choose teaching as a career, and to what extent teacher characteristics and teac her program characteristics had a relationship with t hose motivational factors. Other Limitations of Motivation Theory Research in Education In addition to the aforementioned gaps in current teacher education research studies using motivational theory -lack of conceptual/theoretical model, inconsistencies o f terminology -(altruistic/intrinsic), etc., there are also noted limitations in the literature regarding how teacher characteristics and teacher preparation program characteristics are factored into teacher motivation research. Even among the most recent studies using motivational theory with strong section of people who have diverse experiences in work and life to want to become teachers, and

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82 what sustains them o much knowledge to be gained from further studies using the FIT Choice framework. As mentioned in Chapter 1, currently there are two streams of research that have developed from th e se FIT Choice studies comparing between different groups of preservice teachers and studies that compare the motivational factors with other key constructs. My study falls into the latter category, as the contextual nuances of Florida teachers and the prep aration routes offered to them demand attention in a multifaceted manner. First, using a paint a macro level perspective. This representation can be useful and b eneficial to both researchers and other educational stakeholders to better understand the overall picture of what motivates Florida teachers to become teachers. However, if I were to only treat teacher candidates as one homogeneous group and consolidate th eir scores when reporting findings and/or drawing conclusions, the unique attributes and variances among and between teachers teacher characteristics and teach er preparation program characteristics. This rendition honors the 433 teacher preparation programs in Florida (Milton, & Curva, 2016, p. 4). I seek to uncover any relati onships between the eighteen motivations factors, outlined in socioeconomic status, age, marital status, number of children in a household, prior non teaching work ex perience, and education degree(s). Further, I will establish the relationship, if any, between the motivational factor scores and the length and structure of the program, the delivery mode (online, face to face, or hybrid), hours required in the field, typ e of preparation courses,

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83 and type of license earned. While these elements are not visible in the conceptual model for the instrument (and are sometimes assumed or omitted altogether), it is important that my study delineates the findings by teacher charac teristics and teacher program preparation characteristics. This breadth and depth of information will help to better recruit the type of teachers that best fit the needs of students, schools, and school districts, and provide an insight into what might be the better pathway in which to recruit them. The H istory Evolution, and Stagnation of the Teaching P rofession The following section will explore the history of the teaching profession, the evolution of teacher preparation program characteristics, and the disconcerting stagnation of teacher characteristics and demographics within the American educational, social, and cultural landscape as they relate to the relationship between the dependent variables (motivational factors) and the independent variables (t eacher program characteristics and teacher characteristics). Several motivational factors that influence people to choose teaching as a career such as salary, social status, task difficulty, task expertise, social influences, social dissuasion, and fallba ck career are all deeply rooted in the history of the teaching profession. Additionally how and why teacher preparation programs have changed in the U.S over the last century speaks to how the t variables regressed onto motivational factors in this study: prior non teaching work experience, route to certification, prior educational coursework, length of teacher preparation program, prior teaching experience, and level of education. Finally, the disparities between student and teacher demographics, cultures, and characteristics have reached an inflection point; therefore, the significance of the independent variables of race/ethnicity, g ender, native language, and age regarding teacher demographic s characteristics will be further illuminated.

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84 Historical Overview of Teachers and the Profession The history of the teaching field in America has been long, and rarely regarded highly as tury, many local citizens 12 grades. For example, could transmit a very controlled and set curriculum in a very set and controlled manner. As a result, there were some people who showed no interest in raising the professional status of teachers. However, ther e was a collective movement after the 1840s to formalize teaching science of teaching and the mode of governing a became mo re commonplace, and by the 1890s, normal schools and teaching institutions were [ sic ] ( Ogren, 2005, p. 13, 276). By the late nineteenth century, train high school students (mostly women) to become classroom teachers (Clifford, 1989, p. 296). By the twentieth century, teacher preparation was not only occurring at a more basic level in secondary schools, but also expanding to univer sities. This shift would take teacher education programs and the field of education in a new direction, focusing on graduate and in service teacher training (Labaree, 2008, pp. 293 297). Spearheading this movement were colleges such as Harvard, Teachers Co llege at Columbia University, and the University of Chicago, where a more professional, efficient, and scientific niche was being carved out (Johnson, 1989). banishment

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85 universal across the nation, these elite institutions deepened the wedge in the growing debate of the purpose of teacher education programs. Furthermore, as education became mor e centralized better educated and learned a rhetoric of professionalism, they more and more objected to being ely, many of their objections would fall on deaf ears, as many public school teachers felt they lacked power and influence in society. As Herbst raise their with low salary, social status, and morale, many teachers do not want to take on the challenges of working with struggling students and/or students with whom shared very little social and cultural traits. After World War II, societal pressures and demands for American education compounded from local to state, to even the national level, and teachers and schools were caught in a d that the schools were underfunded, overcrowded, and unprepared for the postwar economy and the atomic age. In the 1950s, critics assailed the and early 196 0s, the Cold War created tensions both inside and outside the classroom regarding dolph, 2002 ). In addition the Civil Rights movements caused some Americans to demand more lib eration and increased federal involvement, first during the 1950s and 1960s and later during the 1980s and 1990s. Public education was crucified after the publica tion of A Nation at Risk (1983), with teachers bearing the b runt of the blame (Rudolph, 2002 ; Schneider, 2012 ). This negative image

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86 in the public eye further devalued the teaching profession, as well as contributed to the struggle to retain high quality te achers. In addition, the implementation of value added modeling (VAM) scores and performance pay increased, which only held teachers more accountable for the success, or lack thereof, of students bolstered the already negative perceptions of teache rs and ( Imig, Wiseman, & Imig 2011 p. 401 ). Teacher preparation programs strived to combat the negative stigma surrounding public education and better prepare their teacher candidates before entering the workforce (Cochran Smith et al ., 2008; Darling Hammond et al. 2005; Kumashiro 2010 ; Levine, 2006). These certification (TRCs), are comprised mainly of coursework and trainings offered throug h universities and state colleges (public or private). These programs typically take 2 3 years beyond an associate's or general education degree to complete, and usually end in a bachelor or e to be, accredited by national and regional boards (e.g. National Council for Accreditation of Teacher Education (NCATE), Council for the Accreditation of Educator Preparation (CAEP)). Aside from program length and location, characteristics of TRCs often include extended clinical experiences with closely integrated coursework, core curriculum taught in context of practice, strong relationships among school and university stakeholders (Darling Hammond, 2010; Darling Hammond, 2013; Darling Hammond & Bransfor d, 2005; NCATE, 2010). Darling Hammond (2008) proclaimed quality o f education in the United States (p. 331).

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87 Addressing Teacher Quantity and Quality: The Rise of Alternative Routes to Certification (ARCs) in the U.S. Despite the growing number colleges and universities that offered teacher education programs, by the mid 1980s, the teaching profession was projected to experience a teacher shortage of over two million teachers within the next two decades (Feistritzer, 2005; Johnson, Birkeland, & Peske, 2005). In addition to the overall quantity of teachers, the more pressin g concern was the lack of quality teachers. As mentioned previously, all of these schisms within private involvement in educational reform (Cohen, 1989). Legislator s and policy makers felt the pressure to enact regulations, and as a result, a great deal of legislation governing teaching certification was altered and made more flexible as one way to address the teacher shortage in the U.S. One consequence of these new regulations was the establishment of alternative routes to short (if any) training and/or education prior to become teacher of record in order to quickly eliminat e the teacher shortage (Friedrich, 2014; Murnane & Steele, 2007). While it is now clear that many of those projections were based on misleading statistics, and the crisis never fully hit all areas of the U.S., the change in the teacher education landscape had already made its permanent mark (Darling Hammond, 2000; Feistritzer, 2005; Johnson, Birkeland, & Peske, 2005). From their conception in the late 1980s and early 1990s, the interest in ARCs surged, in part after the creation of what is now known as the Teach for America Program (TFA) created by Wendy Kopp. In 1989, while she was an undergraduate student at Princeton University, Kopp proposed creating a specialized alternative teaching certification program to improve the poor quality of American educati

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88 undergraduate thesis ( Kopp 2010). Her theory was that the best and brightest students from some of the most elite universities in America would make the best teachers Kopp argued as lo knowledge, it was not necessarily imperative for them to have a formalized background in education to become successful teachers; a six week preparatory course could provi de all the pedagogical and theoretical knowledge that was needed to successfully teach ( Kopp 2010). This new perspective on alternative teaching certification flourished not only out of necessity, but also in popularity for a variety of reasons, and now t here are hundreds of alternative certification programs and pathways, both in the United States and internationally (Blumenreich & Gupta, 2015). ARC programs often carry low financial burden, as well as offer more flexibility and opportunity for teacher candidates whose personal lives are not conducive to the traditional university based setting especially those who were already working in other professions (Johnson, Birkeland, & Pesk e, 2005; Johnson & Kardos, 200 8; Murnane & Steele, 2007). As a result, many ARC programs are catered to fit the needs of professionals in the midst of switching careers who will bring in real world experience. As the next generation of teachers will most l ikely include a higher number of mid career candidates, more flexible teacher preparation program characteristics, especially distance education and use of technology can serve as an essential feature to recruit and train prospective teachers (Johnson & Ka rdos, 2008) In addition, they provide a way to diversify the population of teachers, particularly regarding demographics, traits, and values (Herbst, 1989; Murnane & Steele, 2007; Schneider, 2012 ). Another factor that has led to the continued rise of ARCs was the criticism of, and

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89 decrease in, popularity of TRCs programs. Many prospective students were both dissatisfied and impatient when faced with the traditional routes to certification through a university based program due to the often long, expensive, and overly theoretical teacher preparation options available through traditional university settings (Johnson, Birkeland, & Peske, 2005 ; Johnson & Kardos, 2008 ). There was also a growing concern that TRCs were not attracting a sufficient number of academic ally strong or diverse candidates. SAT scores and GPAs of students entering preservice teacher education were dropping, and the teaching force was remaining homogenous, while the student population diversified (Feistritzer, 2005; Feistritzer & Haar, 2010; Johnson, test score minimum qualifications also create barriers as to who can enter their programs, which has, and can continue to, slow the efforts of increasing the quality and diversity of teacher candidates. As a result, many ARC programs strive to eliminate some of the barriers (e.g. GPA, SAT/ACT scores, etc.) th at TRCs have set in place to provide pathways for students to enter the field, one which otherwise would have been difficult to enter (Abell Foundation, 2001; Feistritzer, 1998; Feistritzer, 2001; Haberman 2004; U.S. Department of Education, 2002; U.S. De partment of Education, 2013). to increase diversity and lessen the teacher shortage while still maintaining the highest standards of teacher education quality (Darlin g Hammond, 2010, Darling Hammond, 2013; Darling Hammond & Bransford, 2005). Furthermore, many advocates of TRCs believe that alternative programs devalue both teacher education and the teaching pr ofession (Kumashiro, 2010 ). ARCs may also increase the cost of recruiting, hiring, and training new teachers because of such high

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90 teacher turnover, as many students leave after only a f ew years (Ingersoll, 1999 ; Lac zko Kerr & Berliner, 2002 ). Taken altogether, the literature examining teacher education pathways st ill provides conflicting data (Zeichner & Conklin, 2015). Humphrey and Wechsler (2007) examine the impact of alternatively certified teachers and their knowledge and skills, and suggest that due to the variation of alternative programs, it is difficult to generalize charac teristics or effects. Shen (1997 ) also had similar results when investigating the effect of alternatively certified teachers on the teaching force and suggest that alternative programs have ) claimed that th ere are strengths and weaknesses to both types of teacher preparation programs. According to Imig, Wiseman, and Imig ( 2011 ), t he disparity in both the qualification and evidence regarding the connections between preparation programmes [ sic ] 401 ). Moreover, these authors also claim : here is little evidence to suggest that there is any one right way to prepare teachers and this has invited e xtraordinary efforts to experiment with alternative models ( Imig, Wiseman, & Imig, 2011, p. 399). Certification Pathways To date there are approximately 3.6 million public sch ool K 12 teachers in the U.S., and third of first time public school teachers hired . entered the profession through an alternative program other than a college campus (Feistritzer, 2011, p. ix ). Forty seven states and the District of Columbia offer over 100 alternative routes to certification (ARCs) implemented in approximately 485 programs (Feistritzer, 2005, p. 1). There are now a multitude of features within ARC programs, and some do not display the

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91 the classroom and can take years to complete (Friedrich, 2014; Murnane & Steele, 2007). (e.g. undergraduate, graduate, specialist) and type of sponsoring institution (e.g. R1 university, community college, school district), which make it dif ficult to distinguish and evaluate from one program to another. There are also a multitude of TRC features from mission statements, admission processes, curriculum, instructional strategies, structure, delivery mode, to teacher candidate population. Becau se there is such a diversity of quality and quantity of preparation programs offered in the United States, many researchers argue that defining critical features of what constitutes Rosenberg and Sindelar track programs to highly specialized programs, and their findings can also be applied to what is considered standard or TRCs: The term ARC has multiple mea nings and applications . .So variable have ARC programs become that treating them as a homogeneous class no longer seems reasonable. In fact, teacher preparation may best be represented as a continuum along which the point where alternative ends and stan dard begins is uncertain. (p. 117 118) years of experience, completion of certification pathway, degree status, amount of coursework, length of practice teaching, a nd amount of preparation has proven more useful and productive (Mason Williams & Gagnon, 2016; Rosenberg and Sindelar, 2005). As Hogan and Bullock

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92 ire to While the proportion of teachers who choose to complete ARC programs is far greater in the U.S., the growing rise of ARC programs may cause the teacher pre paration program since developed into a multi million dollar business and have emerged around the globe, including Australia, China, and Germany, which are also th ree of the countries that have also used the FIT Choice scale to study teacher motivations. It is interesting to note that, to date, none of the studies using the FIT Choice framework completed in Australia, China, or Germany examined the motivations of te achers who went through ARC programs. My study addressed this significant gap in the literature by including participants who went through both TRC and ARC programs, as well as asking them to describe the features of their preparation programs to better de fine the paths beyond the TRC and ARC labels in order to better measure and estimate which teacher program characteristics had a relationship with Florida K 12 motivations to become a teacher. Teacher Student Demographic Disparities in the U.S. To juxtapose diverse student populations with the current lack of diversity in instructional personnel shows an education landscape that wski & Sanders, 2015, p. 102). With the exception of gender, the majority of the U.S. teaching staff mirrors the majority of the traits and values of the hegemonic American dominant culture: predominantly White, Middle class, English speaking, Protestant, heterosexual, while the student body percentage continues to represent more and more culturally diverse students (Spring, 2014, p. 152). As of 2014,

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93 approximately 81.9% of the U.S. teacher population were white, and as of 2014, approximately 51.4% of the U .S. student population were students of color (NCES, 2012, 2014). This gap historically has and will continue to pose many barriers and rifts within a learning environment, as the diverse body of students may often feel a disconnect between themselves and the dominant culture perpetuated by their teachers (Cochran Smith & Dudley Marling 2013 ; Darling Hammond, 2010; Delpit, 2006; Ladson Billings, 1995; Spring, 2014). inc reasing heterogeneity strengthens the need to recruit, educate, and retain effective teachers who can meet, accept, and understand the needs, abilities, and values of these diverse students. Furthermore, this student diversity is not just limited to racial and ethnic backgrounds. Of the third of those students are classified as poverty line (p. 47). There is also an increasing diversity represented by current students regarding native language spoken, special needs and disabilities, along with numerous cultural background differences. It is well documented that there is often a cultural disconnect between the majority of American teachers and their students, which can limit the quality of education provided to them (Carter & Welner, 2013; Hayes and Jurez, 2012; Ladson Billings, 2009; Ladson Billings, 2013; Ross, Bondy, Gallingan e, & Hambacher, 2008; Siddle Walker, 1996, 2011; Ware, 2006). For example, Siddle Walker (2011) asked an audience the larger America . where will you learn to

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94 marginalized students, they have not, and cannot, fully be participants in the public education system. Studies have sugg ested that one way to better address the needs of such diverse student populations is to have a more diverse teaching population, especially regarding race/ethnicity, gender, and language, as it often easier for students to form meaningful relationships wi th their teachers who share common lived experiences and cultural backgrounds (Hrabowski & Sanders, 2015; Lipcon, 2008; Villegas & Davis, 2008). As a result, these students are more likely to have an increase in self esteem, attendance, achievement, and ov erall learning experiences differs, even if he or she shares cultural commonalities and backgrounds. Nevertheless, research that only culturally diverse teachers can be effective in that only culturally diverse students benefit from culturally diverse teachers. As Edwards (2017) states shows that teachers of color contribute to a range of academic outcomes for all students including improved test scores, graduation rates, and post secondary degree at tainment (Dee, 2004; Egalite, Kisida, & Winters, 2015; Klopfenstein, 2005). This body of research indicates that these academic gains hold for White students as well as students of color. The results of these studies support the call for increased efforts to recruit teachers of color and the potential that this 31). However, the literature does emphasize the unique role that diverse teachers provide in improving mor e equitable learning experiences and outcomes for diverse learners. Importantly,

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95 pcon, 2008, p. 541). In order to provide a high quality education, students must be exposed to a variety of learning experiences, people, and cultures. To achieve this goal, there is a need for a more diverse educational workforce. Paths to Becoming a Teac her in Florida If the goal is to use motivations to attract, prepare, and support the best teachers for preparation programs by which current Florida teache rs were recruited and prepared. Over the teacher preparation programs and hold them accountable for their own performance and the (FL De partment of Education, 2017, p. 1). Currently, the state of Florida has four top nationally ranked teaching programs, according to the 2016 U.S. News and World Report. The University of Florida ranked #30, and Florida State University came in at #40, while the University of South Florida and the University of Central Florida tied at #83. Despite the quantity and quality of traditional programs offered in Florida, presently, there are also 433 ARCs offered in the state (Jacobs, 2017). While 47 other states i n America also have growth rates in alternatively certified teachers and one of the most diverse set of alternative (Sass, 2011, p 1). Florida currently recognizes three state approved pathways, from 433 individual programs throughout the state, which grant teaching certification: Initial Teacher Preparation Programs (ITPs), Educator Preparation Institutes (EPIs), and Professional D evelopment Certification Programs (PDCPs). Initial Teacher Preparation (ITP) Programs ITPs a re the more traditional route to teaching certification. These programs, of which there are 373 throughout Florida, are

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96 typically offered at degree granting instit utions, resulting in degrees. Educator Preparation Institute (EPI) EPIs are an alternative route to certification offered through postsecondary institutions such as colleges and universities. These programs focus on certifying prosp field. There currently exist 23 EPI programs in Florida. 68 ITPs and EPIs stem from the Florida College System, 189 from State Universities, and 139 through private colleges or universities. P rofessional Training Option (PTO) or Professional Development Certification Programs (PDCPs) PTOs and PDCPs are alternative route s to certification offered through individual school districts. These 43 programs throughout Florida offer teachers a temporar y license while concurrently teaching and completing their certification program. most subjects requiring only a bachelor's degree major, a passing score on the appropriate Subject Ar ea Examination will qualify you for a Temporary Certificate in that subjec (Jacobs 2017). Moreover, despite the four nationally ranked Colleges of Education in Florida, and even though the University of Florida alone has several nationally ranked educat ion programs, UF has remained in the top five recruiting universities for Teach for America, one of the largest alternative teaching programs in the United States. In fact, in 2012, UF was the second highest contributor to TFA candidates nationwide. The FL DOE awarded TFA funding to increase the number of teaching positions in Florida districts However, in addition to the addition of new pathways available to become a certified teacher in Florida, many existing teacher preparation programs a re continually examining and improving their current programs. Great efforts are being made to create the most effective teachers through the improvement of internships, relationships with professional development schools, university lab schools, and partn erships with private and public organizations.

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97 Figure 2 1. FIT Choice Conceptual Mode l Chapter Summary The literature review in this chapter explored the most current and relevant literature surrounding motivational theory as it related to electing a c areer in the teaching profession. It further explored the validated FIT Choice scale, developed by Watt and Richardson (2007) to leverage a unified, consistent tool, on which to build a foundation of uniform terminology and methodologies. This chapter reve aled the eighteen motivational factors within the FIT Choice scale, and justified each of their inclusion in the scale, as well as their relevance to my study. Chapter 2 also touched on some of the limitations within this literature, which provided the

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98 rat ionale for my study. In Chapter 3, I will provide the methodologies used in this study to design, measure, collect, and analyze the data generated from this study.

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99 CHAPTER 3 METHODOLOGY The purpose of my quantitative, retrospective exploratory study was to use survey research methods using the FIT Choice Scale to explore the initial motivations of Florida public school teachers to elect teaching as a career, and to estimate the extent to which specific teacher characteristics and teacher preparation progr am characteristics had a relationship to particular motivational factors. I endeavored to uncover what influences, beliefs, and values were most important to Florida teachers in choosing a career in teaching, categorized into certain typologies (e.g. gende r, race, certification) based on their personal characteristics and/or the teacher preparation program in which they participated. To achieve this goal, I used survey research methods grounded in both expectancy value theory and a vetted framework the FIT Choice Scale a measurement tool that has repeatedly reported high validity and reliability of scores in a variety of contexts (Richardson, Karabenick, & Watt, 2014; Watt et al., 2012; Watt, Richardson, & Smith, 2017). I used consistent terminology found t hroughout the literature base; however, an exploratory retrospective design was chosen because there was little empirically based evidence on which to build this study in this specific context Florida K 12 public school teachers. The exploratory design ex amined correlations among various variables and constructs in order to provide thought leadership for future initiatives or strategies in teacher education, as well as field of education at large with regard as to how to best recruit, and ultimately prepar e and retain teachers in the state of Florida (NSF, 2013, p. 9). These intentions aligned with the National compelling case that the proposed research will generate impor tant knowledge to inform the

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100 2013, p. 9). between two or more variables usin Creswell, 2010, p.173) ; as such, I did not attempt to control or manipulate the variables in this study, or the pa My study also was retrospective because I asked parti cipants to reflect upon their past motivations for choosing a career in teaching. The following research questions guided my research study. Research Questions RQ 1 What were the motivations of Florida K 12 public school teachers to choose teaching as a career, as measured by the FIT Choice Scale? RQ 2 To what extent do teacher characteristics (age, race/ethnicity, gender, native language, prior non teaching work experience) and teacher program characteristics route to certification, prior educational c oursework, prior teaching experience, level of education, and length of teacher preparation program) have a relationship with each motivational factor score? Target Population The population of interest in this study was current 2016 2017 Florida public school teachers ( N =173,396). These Florida teachers comprised an extremely heterogeneous population, with diverse demographics, characteristics and backgrounds, including various teacher preparation programs. These teachers taught in various subject areas, at different stages of their career, with different locations of their P 12 schooling in 67 counties. Theoretical Framework Watt and Richardson (2006; 2007) developed the FIT Choice Scale to measure different tions for choosing a teaching career. The FIT Choice instrument was well suited for my study, as it draws together recurring themes of several bodies of literature: motivational theory, education, teaching career choices, self perceptions and self

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101 efficacy as well as broad career choice research. In creating the FIT Choice conceptual model and scale, Watt and Richardson (2006; 2007) situated these recurring themes within Wigfield ational model developing both the FIT c omprehensible and coherent model to guide systematic investigation into the question of why the FIT Choice P roject ( www .fitchoice.org ), and the continuity of the use of their framework and instrument have helped to address some of the aforementioned limitations in the field. Scores indicated high construct validity, with factor loadings ranging from .50 to .95 at the firs t order level, and .52 to .93 at the higher order level. The sample also displayed acceptable internal ties ranging between .62 and .92 Typically accepted factor loa dings are above .03 (Kline, 20 09 ) This framework has been widely used in a range of cultural settings and different samples, and many studies which have used the FIT Choice Scale have reported similar high levels of construct validity and internal consistency when replicated and used in other schools, settings, or countries with preservice teachers. In addition to Australia, the FIT Choice Scale has been used in Austria, China, Croatia, Estonia, Germany, Indonesia, the Netherlands, Norway, the Republic of Ireland, Switzerland, and the United States (Akar, 2012; Berger & D'Ascoli, 2012; Brandmo & Nesje 2017; Fokkens Bruinsma & Canrinus, 2012; Gratatcs, Lpez Gmez, 2012; Kilin et al., 2012; Knig & Rothland, 2012; Lin et al., 2012; Richardson & Watt, 2010;

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102 Watt & Richardson, 2007; Taimalu, Luik, & Tht, 2017; Watt et al., 2012; Yu & Bieger, 2013). Most FIT Choice studies conducted within the U.S. have used samples with preservice teachers, with the exception of three; it has been used twice with samples of i n service (current teachers) in the U.S with teachers in a Western state (Leech & Haug, 2015; Leech, Haug, Ridgewell, & Ruben, 2018), and once with students in two urban high schools in a Western state (Leech, Haug, & Bianco, 2015). These studies have foun d that the FIT Choice Scale predicts high school Choice Scale had not been used in this population ( current K 12 Florida public school teachers ) or a similar population from which to compare. Thus, this study extends the literature by utilizing the FIT Choice Scale with in service teachers elsewhere in the United States, in the state of Florida, and by asking new questions from the scale data, specifically related to unique attributes of teacher and teacher preparation program characteristics, (e.g. related to gender, race, native language, alternative certification, etc.). The contextual nuances of Florida teachers and the preparation routes offered to them demand attention in a multifaceted manner, and my research methods appropriated reflected these characteristics. First, using a broad approach, I provided a summarized representation o f This representation could be useful and beneficial to both researchers and other educational stakeholders to better understand the overall picture of what motivates Florida te achers to become teachers. However, if I were to only treat teacher candidates as one homogeneous group and consolidate their scores when reporting findings and/or drawing conclusions, the unique attributes and variances among and between teachers would be

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103 unique attributes of teacher characteristics and teacher preparation program characteristics. This div ersity of the 473 teacher preparat ion programs in Florida (Milton & Curva, 2016, p. 4). While these elements are not visible in the conceptual model for the instrument (and are sometimes assumed or omitted altogether), it is important that my study delinea tes the findings by teacher characteristics and teacher program preparation characteristics. This breadth and depth of information will help to better recruit, prepare, support, and retain the type of teachers that best fit the needs of Florida students, s chools, and school districts. Method I used survey research methods to collect data from current Florida K 12 public school teachers who taught during the 2016 2017 school year regarding the motivational factors that had influenced them in choosing teachin g as a career. A public information request was submitted via email to the Florida Department of Education (FLDOE) PERA Office (Bureau of PK 20 Education Reporting and Accessibility) to access the 2016 2017 Florida teacher database, which contained the ema il addresses I used to contact participants. An electronic survey was distributed to all 173,396 current public school Florida teachers in May and June of 2017 to their school email addresses via a link in Qualtrics. The first section of the survey includ FIT Choice Scale about teaching, and 3) decision to become a teacher. Additional items measuring teacher characteristics and teache r preparation program characteristics were also included on the survey. These items were extracted from 1) the National Teacher and Principal Survey (NTPS), the background/demograp

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104 created by Leech and Haug (2015), who used the FIT Choice survey in the United States with in service teachers. The survey contained a total of 152 items. As this study was retrospective in nature, participants (current Florida public school teachers) were asked to think back to when they first made the choice to become a teacher, mindset and subs equent responses about the past for the first 58 items (questions), the survey provided the following prompt: Please remember to think back to your initial motivations when you first chose teaching as a career. Data Collection Data were collected throu gh participants self reporting their motivations for electing teaching as a career choice, specifically the factors that influenced their decision (e.g. their self perceptions of teaching ability, the ability to shape the future of children/adolescents, en hance social equity, etc.); their beliefs about teaching (e.g. expertise, difficulty, social status); and their ultimate decision to become a teacher (e.g. experiences of social dissuasion along with satisfaction with the choice of a teaching career). Part icipants also self reported their demographics, characteristics, and teacher preparation program characteristics. Choice survey was distributed via paper and pencil, but I adapted the survey to be distributed elec addresses via a link in Qualtrics Insight Platform, an electronic data capture tool. There were several advantages to distributing the survey electronically as opposed to in person using paper. Using Qualtrics allowed m e to distribute the survey more efficiently, timely, and to more participants in a short amount of time. I was also able to create personal links for each participant, as well as track participation. Additionally, there was the benefit of a rapid turnaroun d in data collection (Babbie, 2012; Creswell, 2014, p. 157). The possible disadvantages

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105 of utilizing an online survey tool could be a lower response rate than an in person, paper and pencil instrument. Through Qualtrics, data were collected, organized, man aged and secure, as I sent the initial email to participants on May 5 th prior to when teachers dismissed for the summer break. The survey was sent to their school assigned email account, to be completed at their convenience. Two follow up emails were sent every two weeks after the initial survey as a reminder to complete the survey in an appropriate timeframe until the middle of June. This timeline was based on previous studies and survey design method literature (Dillman et al., 2009; Dillman, Smyth, & Christian, 2014). Dillman, Smyth, and Christia n (2014) suggest considering typically low. A personalized m essage was included (Appendix F ) for two main reasons: 1) to clearly explain the study and participation and 2) and personalization has been shown to increase response rates (Dillman et al., 2009). I also offered participants an incentive to complete the survey, as incentives have been shown as another way to improve survey response rates (Dillman, Smyth, & Christia n 2014). I communicated to the participants in both the survey overview and email requests for participation that every 25 th resp ondent up to the first 5 (125 th ) who provided his or her information was provided a gift card. In completing my study, I adhered to the American Educational Research Association (IRB) guidelines. Regarding consent to participate in my study, all participants were required to view and accept the informed consent form provided on page one of the survey via the Qualtrics link before they could proceed and access the rest of the surve y. Other than pregnant women, the participants in this study were not projected to be considered of special needs or of vulnerable populations, and

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106 there were no foreseen risks for study participation. Participants were informed that participation was comp anonymous. Data were, and will continue to be stored appropriately in a secure manner for three years, as per the ethical standards for human subjects in research as set fort h in the American Psychological Association Ethical Principles of Psychologists and Code of Conduct. Survey Responses I received 10,039 total responses from the 2016 20 17 Florida K 12 public school teacher population of 174,396, or a response rate of 5.6% A ll scores from participants who responded to at least three of the 58 Likert scale items were included in the analysis, as three survey items could measure the majority of the motivational factors Of the 10,039 original responses, 8,420 met this criter ion and were chosen for analysis. For some factors, the full information was available. When missingness existed for a factor, I used pairwise deletion in SPSS, which is a method that is best used to account for data that is missing at random (MAR), and co mputes the basis of all cases with non missing values for that particular pair of ata set as possible (Marsh, 1998 p. 23). If data re the respondent provided an answer ( Keith, 2015, p. 526) Of the 8,420 responses used in analysis, missing ness was belo w 8 %. Maximum Likelihood Robust (MLR) es timator was also used to analyze my model by using Mplus 7 (Muthn & Muthn, 2005 2012) so that all available data from the 8,420 responses could be used in this study.

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107 Participant Demographics The participants in my study were represent ed across 65 of the 67 Florida counties and districts (excluding Washington and Monroe counties) Participants reported their own teacher characteristics, demographics, and teacher program characteri stics, as summarized in Table 3 1 below, as well as outlined in detail in Appendix D. Of the 8,420 respondents, 79.8% identified their gender as female, 18.5% identified as male, 1.5% preferred not to answer, while 0.2% self identity due to my social justice and equity stance as a researcher, and to date, no other researcher using the FIT Choice survey has collected and/or reported such data. Ages of respondents ranged from seventeen to eighty four, and the mean age was calcu lated at forty seven years of age. Sixty four (64%) of respondents reported they identified their race/ethnicity as White, which may have included some of the Hispanic or Latino respondents, as the response rate reporting Hispanic was 12.9%. Over 8% of par ticipants identified as Black, and 1% identified as Asian, Hawaiian, or Other Pacific Islander; American Indian or Alaska Native; or Other, which combined for over 12%. Finally, 15% claimed Multiple races/ethnicities. Native language was self reported in t his study, showing a vast majority, at over 90% of respondents, reporting English as a first language. Spanish was the second highest reported spoken native language, at seven (7%), and finally French or Creole, Multiple languages, or some other language a ll reported around one (1%). Education information was also collected in this study, indicating that the population was split almost evenly 53% During their degree completion, 60% reported they had taken education coursework, and 40% had no education coursework in their collegiate studies. Respondents reported teacher preparation programs of both Alternative 27% and Traditional 73%. Duration of these programs

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108 ranged from just one week up to a claimed 30+ years. A six year preparation program was the longest period reported by respondents. specific work experience, and non teaching work experience. Seventy one per cent (71%) of respondents claimed they had prior teaching experience before electing teaching as a career, while 29% reported none. Seventy three percent (73%) of respondents claimed they had prior non teaching working experience before electing teaching a s a career, while 27% reported none. The range of this non teaching work experience varied greatly from just a few months up to sixty years, with an average non teaching work experience span of over ten years. Please see Table 3 1 below for further informa tion. Table 3 1. Demographics of Participants Age Gender Native Language Race Range 17 84 years Male 18.5% English 90.1% White 64.0% Mean 47 years Female 79.8% Spanish 7.1% Hispanic 0.3% Other 0.2% Multiple 1.0% Black 8.4% Prefer not to answer 1.5% French or Creole 0.5% Asian 0.8% Other 1.4% Multiple 14.4% Other 12.2% Education Route to Certification Degree Level Coursework Length of Teacher Preparation Program Prior to Teaching Alternativ e 27% 53% Prior Education Coursework 60% Range 1 1768 weeks Traditional 73% Graduate 47% No Prior Education Coursework 40% Mean 112 weeks

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109 Table 3 1. Continued Age Gender Native Language Race Work Experience Prior Teaching Experience 71% Have Prior Non Teaching Experience 73% Range .25 60 years No Prior Teaching Experience 29% No Non Teaching Experience 27% Mean 10.6 years Variables and Scales The FIT Choice (Factors Influencing Teaching Choice) scale (Watt & Richardson, 2007) is based on a conceptual model that contains three main sub scales, motivations for teaching (12 factors), perceptions about the profession (4 factors), reasons to become a teacher (2 factors). The FIT Choice Scale contains four higher order factors and seven first or der factors. The first scale with one open ended prompt, and 58 radio response questions regarding their 1) influences to become a teacher, 2) beliefs about teaching, and 3) decision to become a teacher. Regarding the items related to the influences to become a teacher, respondents were asked to indicate their strength of agreement on a Likert scale from 1 ( n ot at all important ) to 7 ( extremely important ). In the section of questions related to beliefs about teaching, as well as decision to become a teacher, respondents were asked to indicate their strength of agreement on a Likert scale from 1 ( not at all ) to 7 ( extremely ) as to how much these factors influenced their choice of teaching as a career. Dependent Variables : Motivational Factors There were thirteen dependent variables examined in this study: self perceptions of teaching ability, intrinsic career v alue, fallback career, prior teaching and learning experiences, social influences, personal utility value, social utility value, expertise, difficulty, social status,

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110 salary, social dissuasion, and satisfaction with choice. Each variable is described below in more detail. Influential factors The first section of the FIT Choice Scale is Influential Factors (Watt & Richardson, 2006), which assesses the influential factors affecting respondents' choice of a career in teaching. This section contains 38 total it ems or questions. There are 5 first order factors and 2 higher order factors in this section. The five first order factors are self perceptions of teaching ability ) ; intrinsic career value (e.g. I have always wanted to be a teacher ) ; fallback career (e.g. I was not accepted into my first choice career ) ; prior teaching and learning experiences (e.g. I have had positive learning experiences ) ; and social influences (e.g. My family thinks I should become a t eacher ). All 5 first order factors are each measured with 3 items. The first higher order factor is personal utility value which contains 3 sub factors: job security, time for family, and job transferability Job security is measured by 3 items (e.g. T eaching will offer a steady career path ); time for family ( Teaching hours will fit the responsibilities of having a family ) is measured by 5 items, and job transferability (e.g. A teaching qualification is recognized everywhere ) is measured by 3 items As such, the personal utility value factor is measured by 11 items. The second higher order factor is social utility value, which contains 4 first order factors: shape future of children/adolescents (e.g. Teaching will allow me to shape child and adole scent values ) enhance social equity (e.g. Teaching will allow me to benefit the social disadvantaged ) make social contribution (e.g. Teaching will allow me to provide a service to society ) and work with children/adolescents (e.g. I like working wi th children and adolescents ). All 4 sub factors are each measured by 3 items; 12 items total.

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111 Beliefs about teaching The second section of the FIT Choice Scale is Beliefs about Teaching. It has 2 higher order factors, task demand and task return which ea ch contains 2 first order factors. Task demand comprises expertise (e.g. Do you think teaching requires high level of expert knowledge? ) and difficulty/high demand (e.g. Do you think teachers have a heavy workload? ) with 3 items each. Task return cons ists of social status measured by 6 items (e.g. Do you think teachers are perceived as professionals? and Do you think teaching is a well respected career? ). Salary is measured by 2 items (e.g. Do you think teachers earn a good salary? ). There are 14 However, for the purposes of data analysis, there was not good model fit for the 2 higher order factors (See Table 3 2). T herefore, the 4 subsumed factors were analyzed separately as first orde r factors. Your decision to become a teacher The third section of the FIT Choice Scale is Your Decision to Become a Teacher It has 2 factors, social dissuasion (e.g. Did others tell you teaching was not a good career choice? ), measured by 3 items, and satisfaction with choice ( How satisfied are you with your choice of becoming a teacher? ), measured by 3 items This section assesses experiences of social dissuasion along with satisfaction with the choice of a teaching career. While this section contains 6 items in the survey, only 5 items were used in analysis, as one item was omitted from satisfaction with choice due to poor model fit. Independent Variables: Teacher Characteristics and Teacher Preparation Program Characteristics The following items were included not just for demographic purposes, but some specifically to address the gap in the literature and the justification for Research Question 2, regarding the need for more studies examining these variables of interest in conjunction with the

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112 FIT Cho ice Scale and other research on the motivations for choosing teaching as a career (Heinz, 2015; Leech, 2015). When teacher candidates and/or their teacher preparation programs are treated as homogeneous groups and amalgamated together, it makes it difficul t to draw accurate comparisons/conclusions among studies. When the nuances of these variables are ignored, or ill defined, the ability to explain phenomena is limited. Furthermore, research that grounds itself on eaker and more likely to draw false conclusions. The independent variables measuring teacher demographics, background characteristics, and teacher preparation program characteristics were adapted from the National Teacher and Principal Survey (NTPS) regard economic status, gender, location of their P 12 schooling (e.g., urban, rural), prior work experience in education, certification routes, and teacher program characteristics. The teacher preparation program structur es addressed in the survey contained the number of hours of field experience required, type of preparation courses, and type of license earned. Additionally, I included some s (2015) studies in the surve y (the complete survey is provided in Appendix F). The ten (10) independent variables analyzed were: 1. Race/Ethnicity (white, black, other) 2. Gender (female, male, other) 3. Native Language (English, Spanish, other) 4. Age 5. Prior Non Teaching Work Experience (Y/N) 6. Route to Certification: Alternative or Traditional (Y/N) 7. Prior Educational Coursework (Y/N) 8. Length of Program (in weeks) 9. Prior Teaching Experienc e (Y/N) 10. Level of Education, Graduate (Y/N)

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113 Teacher c haracteristics Based on important nuances and diversity of public Florida public K 12 teachers, I asked participants to provide additional information regarding the personal and demographic infor mation in order to have a clearer understanding of, and ability to measure, how participants identified themselves The following section items focused on the characteristics of the teachers who participated in this study Age. Data regarding age were measu red by one item on a continuous scale by recording day, month, and year. Race and ethnicity. Data regarding race and ethnicity were measured by two items placing participants into 6 major categories of race and ethnicity. Native language Data regarding n ative language was measured by one item, text entry Gender Data regarding gender were measured by one item with four choices: male, female, and other, and prefer not to answer. ended tex t entry which was intentionally added by the researcher Prior work experience Data regarding prior work experience were collected from participants who indicated that they had previously pursued another career or had prior work experience before becomi ng a teacher were asked to list details of that career. Teacher p reparation p rogram c haracteristics i tems Based on important nuances of teacher preparation pathways discussed in the aforementioned literature, as well as the quantity and diversity of teach er preparation pathways offered in option indicating if they completed an ARC in the teacher and teacher program characteristics section of the survey. Ins tead, I asked participants to provide additional information regarding

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114 the features of their program as described above in order to have a clearer understanding of, and ability to measure, what type of program features that probed into these specific teach er program characteristics. The following section items focused on the characteristics of the teacher preparation programs participants completed. Route to Certificat ion: Alternative or Traditional, (Y/N) Data regarding teaching certification were measur ed by one teaching through an alternative route to certification program? An alternative route to certification program is a program that was designed to expedite the transition of nonteachers to a teaching ca reer for example, a state, district, or university alternative route to certification program. Prior Educational Coursework (Y/N) Data regarding prior coursework in Education were measured by one f teaching, did Length of Program (in weeks) Data regarding length of teacher preparation program were measured by one of your teac her preparation program PRIOR to you becoming a teacher of record? Please Prior Teaching Experience (Y/N) Data regarding having prior experience teaching were measured by one ave any student teaching (sometimes calls practice teaching or an internship) prior Level of Education, Graduate (Y/N) Data regarding level of education and whether a graduate degree was earned were measured by one item wit level degree? If you have more than one, information about additional degrees will be asked later. Validity and Reliability In order to support my claims that my study maintained high stand ards for rigor in the design, measurement, and analysis for my study, I provided evidence of the validity of my study to maintain that the results of my study were both reliable and allowed for valid inferences (Kline, 2009). I endeavored to minimize the t hreats to validity in my study in order to enhance the degree to which I could generalize my findings to the larger population (Florida K 12 public school teachers) as well as the degree to which the inferences and interpretations I drew from the

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115 data with in my study were accurate. T o sustain high external validity, my design was created to be such that the results would hold true over variations in persons, treatments, settings, outcomes, and measures (Kline, 2009). High external validity of a research des ign increases the likelihood that one could accurately generalize findings to a population; however, given the design of this study, both population and sample validity were a potential threat to the external validity of my study. However there were some poetential threats to the validity of my study. Because I chose necessarily representative of the population ( Kline, 2009 p.68). However, one way I mitigated some of the threat to validity population (if such a profile exists) in order to show that a convenience sample is not grossly sample to the demographics of the larger population current Florida public school teachers as a whole). The demographics of my sample were, indeed, similar in nature to the teacher population in Florida. Another potential external validity threat concerned Florida K 12 public schools. Although the teachers received a link to the survey electronically, they received it through their school email address and most likely accessed it while they were at their place of employment. Addit ionally, t he time of yea r I distributed the survey, May could have affected the response rate as it was the end of the academic school year There was the potential that the participants would respond differently if they were to receive this su rvey in a different setting, timing, or manner (Kline, 2009). Other threats to the validity of my study, and the degree which I could provide sound evidence to support the accurate interpretations I inferred from the motivational factor scores were due to self selec tion and voluntary participation in my study

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116 ( AERA, APA, & NCME, 2014 ). There could be a difference of responses between the type of people who agree to do surveys/experiments and the type of people who do not and that all responses were honest and accura te. One other potential validity threat was that there were no external factors that u nduly influenced the responses. In order to enhance content validity, I used predetermined items from the National Teacher and Principal Survey (NTPS) and questions from characteristic variables. relationship between the conte I also sought feedback about the content of my survey from current teachers ( AERA, APA, & NCME, 2014 p. 14) Because the questionnaire had not been used in past research studies with either preserv ice or current Florid a teachers, a select group of ten current teachers from various areas in Florida, and one in Georgia, were asked to volunteer to provide informal feedback on the questionnaire prior to distribution to the whole population. These volunt eers responded to a list of questions I provided to assess appropriateness of the questionnaire wording, visual design and layout, as well as question order. These teachers also provided feedback with regard to the time it took to complete the survey, the level of difficulty, and overall content coherence. Examples of specific questions/prompts were 1) Do you think the gift card would incentivize you? 2) How long did it take you to complete the survey 3) Were there any confusing questions? 4) Any other feed back. Some examples were confusion and difficulty when reporting the specifics regarding certification and subject area, duration of teacher preparedness, questions or information that seemed redundant, and typos within the survey. In addition to construct ive feedback, g eneral positive comments were also provided, such as like your research is spot on with what

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11 7 needs to be looked at in this career T wording and order of a small number of items in the teacher demographics and teacher program characteristics sections to provide further enhance content validity. Construct Validity and Reliability I also endeavored to provide evidence for sound construct validity of data produced by the FIT Choice Scal e, the adequacy of the model in explaining the data and the correct measurement of the variables in this study I chose factor analysis specifically confi rmatory factor analysis, ( CFA ) as a way to measure and provide evidence for the construct validity of validity and reliability of my test scores. T he majority of the CFA analyses were completed using Mplus software versi on 7 (Muthn & Muthn, 1998 2012 ). Factor analysis is often used to provide evidence for the internal validity of tests, surveys, or othe r instruments, particularly convergent and divergent validity because it helps answer questions about the constructs measured by a set of items. (Keith, 2015, p. 332). In other words, items that correlate highly with each other (determined by their weights or scales) are placed or nested on one factor, while items that correlate at a low level with each other are placed or nested on different facto I assessed the reliability of my data to estimate the consistency of measu rement, and I used the 2015, p. 53), as well as omega coefficients. The d ata produced by this model displayed acceptable

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118 and 0.948, and omega coefficients ranging betwee n 0.655 and 0.949 (see Table 3 2 for full results). T able 3 2 T he FIT Choice Scale Higher order factor First order factor Sample item Omega coefficient alpha Number of Items Influential Factors Self perceptions of teaching ability I have the qualities of a good teacher .795 .790 3 Personal utility value Intrinsic career value Fallback career I have always wanted to be a teacher I was not accepted into my first choice career .694 .655 .846 .686 .614 .754 3 3 11 T ime for family Teaching hours will fit the responsibilities of having a family .734 .831 5 Job transferability Job security A teaching qualification is recognized everywhere Teaching will offer a steady career path .703 .738 .679 .824 3 3 Social u tility value Shape future of children/adolescents Teaching will allow me to shape child and adolescent values .904 .877 .907 .883 12 3 Enhance social equity Teaching will allow me to benefit the social disadvantaged .848 .897 3 Make social c ontribution Teaching will allow me to provide a service to society .835 .872 3 Work with children/adolescents I like working with children and adolescents .832 .900 3 Prior teaching and learning experiences I have had positive learning experienc es .889 .876 3 Social influences My family thinks I should become a teacher .821 .821 3

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119 Table 3 2. Continued. 2. Beliefs about teaching Expertise Do you think teaching requires high level of expert knowledge? .842 .838 3 Difficulty Do y ou think teachers have a heavy workload? .833 .829 3 Social status Do you believe teaching is a well respected career? .896 .894 6 Salary Do you think teachers earn a good salary? .872 .870 2 3. Your decision to become a teacher Social Dissu asion Were you encouraged to pursue careers other than teaching? .759 .739 3 *Satisfaction with choice How happy are you with your decision to become a teacher? .949 .948 3 Due to poor model fit, one item was removed from satisfaction with choice (Q67) to establish a higher model fit within the CFA model. CFA was also used to provide evidence of validity with regard to whether the measured constructs/factors from my sample were consistent and whether or not the measured variables (first and higher or der factors) accurately represented the number of constructs measured. While g the (Keith, 2015, p. 333; 387). Assumptions of CFA were assessed, and I embraced the threshold that acceptable standardized factor loadings should be higher than .30 as scores higher than the 0.3 usually indicate factor loadings have high construct validity (Keith, 2015). Additionall y, my factor loadings were model, which ranged from .50 to .95 at the first order level, and .52 to .93 at the higher order level. However, I determined that there was one item that did not fit well and was below the 0.3 cutoff; therefore th at item, Question 67 (Q67; 0.227 ), was removed from the analysis of sat isfaction with choice Additionally, I only had two higher order factors in my analysis model,

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120 social utility value and personal utility value as opposed to the having four higher order factors in the original model by Watt and Richardson. Appendices A, B and C provide more detailed information and evidence for the validity and reliability of scores as measured by the FIT Choice in this study. Appendix A contains the visual representations/diagrams of the CFA model Appendix B displays the output of the c orrelation matrices, and Appendix C provides the output of multicollinearity tests, histograms, p plots, and scatterplot diagrams. I also r eported more specific model fit information about the models as Kline (2015) recommends: the Chi squared test (diff erence between expected and observed covariance matrices), the root mean square error of approximation (RMSEA), the comparative fit index (CFI) (examining the discrepancy between the data and the hypothesized model, residual correlations), and the standard ized root mean square residual (SRMR). In this study, there was good model fit to the data for the ma jority of the items and factors ( see Table 3 3 for full results ) Table 3 3 Goodness of fit statistics for measurement invariance model across alternativ ely and traditionally certified group Factors df CFI TLI RMSEA BIC AIC Ability 2993.123 3 1.00 0.05 73913.186 73849.875 Intrinsic 3197.900 3 1.00 1.00 0.00 87803.047 87739.704 Fallback 1032.040 3 1.00 1.00 0.00 92099.890 92036.553 Personal Utility 29493.473 5 0.923 0.896 0.00 355564.476 35531 1.103 Social Utility 38069.295 66 0.952 0.937 0.00 298987.615 298706.233 Prior Teaching & Learning 4533.444 3 1.00 1.00 0.00 80534.452 80471.213 Social Influences 4729.456 3 1.00 1.00 0.00 99195.595 99132.256 Expertise 4517.923 3 1.00 1.00 0.00 81681.6 73 81618.894 Difficulty 4586.604 3 1.00 1.00 0.00 90896.540 90833.614 Social Status 15355.222 15 0.959 0.932 0.00 169894.183 169768.330 **Salary Social Dissuasion 3523.436 3 1.00 1.00 0.00 97101.204 97038.489 **Satisfaction All stically significant at p < .00 1 * Salary and Satisfaction with career choice were not included as they contain only two items.

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121 Data Analysis Data collected via Qualtrics were converted into a CSV file for data analysis. Once data were succ essf ully collected, the data were cleaned and coded as numbered data for analysis using statistical procedures appropriately (e.g. converting letters or words into numbers, such as male, fema le, other, coded into 0, 1, 2,) (Creswell, 2014). I ncomplete or m issing data was appropriate handled (pairwise deletion). While the majority of the analyses were completed in IBM Statistical Package for the S ocial Sciences (SPSS) version 25 the cleaning and coding of data require d the additional use of R Statistical so ftware Exploratory data analysis (EDA) and tests for normality were completed (Kline, 2009; Leech, Barrett, & Morgan, 2015, p. 25). statistical analysis. Using tests such as box plots and frequency pol ygons, and examining the means standard deviations, ranges, and outliers determined if the variables were approximately normally distributed and revealed features of the dataset (e.g. symmetry, skew, central tendency, variability, etc.); possible errors in the data (e.g. missing values); and determined if I needed to transform the data set. I clarified that the assumptions for my inferential statistic models were met (e.g. homogeneity of variance, normality, linearity, independence of observations). Resear ch Question 1: Descriptive Statistics After the initial preliminary analyses were completed, t o answer the first research q u estion, descriptive statistics were used to measure analyze and interpret the motivational factor variable scores to the 58 Likert scale items (on a scale of 1 7) for each participant on the survey I measured the total overall mean scores and standard deviations to examine Florida K motivations for choosing teaching as a career, their perceptions of the pr ofession, and their s atisfaction with career choice. I also displayed summaries of data visually

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122 in tables or diagrams (e.g. bar graphs, box plots, histograms, etc.) to construct visual meaning from the descriptive data. Research Question 2: Multiple Regr ession Models Although I was not testing a hypothesis in this study association (or relationship) between two or more variables using the statistical procedure of (Clark & Creswell, 2010, p.173). T herefore, in order t o answer the second research que stion, inferential statistics s pecifically si multaneous multiple regression were used to estimate the association of the independent variables (teacher characteristics and teacher preparation program char acteristics) on the dependent variables (motivational factors). I analyzed data from the multiple regression models to estimate if these variables were, and to what extent, related (Keith, 2015, p. 539). In the context of this study the assumption was tha t these IVs of interest (e.g. race, gender, age, type of preparati on route) did not have a relationship on the DVs ( motivational factor s), and the scores from my analysis provided evidence as to what extent this assumption was met. Additionally, these infe rential statistical data a ddressed the directional semi partial correlation s between teacher characteristics and teacher program characteristics (IVs) on each motivational factor score (DVs). There are several key assumptions to MR, and as Keith (2015) po sits, if these R 2 the regression coefficients, standard errors, tests of statistical significance (p. 188). uidelines, underlying assumptions of multiple regression are listed below (p. 188) : 1. The dependent variable is a linear function of the independent variables

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123 2. Each person (or other observation) should be drawn independently from the population. This assump tion means that the errors for each person are independent from those of others. 3. The variance of the errors is not a function of any of the independent variables. The dispersion of values around the regression line should remain fairly constant for all val ues of X. This assumption is referred to as homoscedasticity. 4. The errors are normally distributed. I conducted e xploratory data analysis (EDA) to provide evidence that assumptions 1 4 were met. For example, multicollinearity was not violated, as my toleran ce values were low (close to 1), and my VIF values were less than 7 and these values were within the acceptable range (Leech, Barrett, & Morgan, 2015). Results from these tests and other tests are reported in the figures at the end of the Chapter. Then I proceeded with statistical analysis using simultaneous MR. While there are many types of MR methods, simultaneous multiple regression was the best choice for my study because there were neither existing theories within the FIT Choice literature on which t o base which factors should be included, nor evidence to support how these variables were related within this specific context. Other types of regression, such as sequential, hierarchical, or block, would be more appropriate if I (or other researchers) had preconceived notions regarding what variables to include in what order, and what outcomes to expect (Leech, Barrett, and Morgan, 2015 p. 109 110). The number of researchers who are using FIT Choice Scale is rapidly increasing, and simultaneously more com plex methods are being used in this research to further deepen and expand the use, reliability, and validity of this scale. However, exc (2017) study in Norway, multiple regression had not been previously been used in FIT Choice studies, and their model varied drastically from mine.

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124 When conducting MR, more than one IV is specified in the model, therefore there are multiple slopes, or partial slopes, for multiple independent variables. Additionally, there is still o nly one intercept (the predicted y associated with all X s equal 0) (Keith, 2015; Leech, Barrett, & Morgan, 2015). In MR analysis, the variance in the DV has been removed, or taken out by more than one IV, so the slopes, or partial slopes, are usually small er than bivariate correlations Thus, the standardized slopes are similar to semi partial correlations (although not equal); therefore, I used standardized Beta ( ) in order to control for the variance of other the variables. Additionally, when using MR, the predicted rate of change is one unit change in Y given a one unit change in X, co ntrolling for the effect of other variable(s) (Keith, 2015; Leech, Barrett, & Morgan, 2015). Additionally, MR analysis allowed me to measure multiple independent variables (IVs) on a particular dependent variable (DV) (Keith, 2015; Leech, Barrett, & Morgan, 2015). Given my large data set, with both continuous and categorical variab les, MR was an appropriate analysis model because the aim of this non (Kline, 2009, p. 42). As aforementioned, one of the advantages of using MR, is its ability to explain how multiple variables predicted or had a relationship with other variables, as well as estimate the variation within the variables themselves. of MR, we MR, I was able to explain not just one possible influence or prediction of a motivational factor (e.g. what influence does age have on the motivational factor of job secu rity?), but also explain how other variables, as well as variation within the variables themselves, could explain the prediction of the motivational factor scores for both continuous and categoric al variables (Keith,

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125 2015 ). In other words, I was able to re gress motivation, or more specifically scores on motivational factors, on gender, age, race, degree, etc. all at the same time. Finally, because when one uses MR there is an implication that there is a model in place, my MR models helped appropriately guid e the analyses using the FIT C hoice model (Keith, 2015 ). When first choosing the model, I ran a pilot test in the summer of 2017 using a data set of 3,500 respondents. I tested a variety of independent variables (~20) and recorded their association with th e dependent variables (motivational factors). Interactions were also tested with this data, and I chose variables based on the existing education literature. After finalizing the data set of 8,420 results, many of the variables were omitted due to not havi ng a statistically significant relationship with the motivational factors scores For example, age when first began teaching was one of the variables removed. This variable was included to try to capture the possible extent to which the characteristic of p eople who entered teaching later in their li ves, perhaps as career switchers, had a relationship with motivational factor scores This process was repeated until I pared the independent variables down to the final 10 as seen in the current models. Thirtee n (13) multiple regression models were used to estimate the prediction that (10) teacher and teacher preparation program characteristics had on a particular motivation factor, the outcome variable in this regression analysis. The ten (10) predictor variabl es were: 1. Race/Ethnicity (white, black, other) 2. Gender (female, male, other) 3. Native Language (English, Spanish, other) 4. Age 5. Prior Non Teaching Work Experience (Y/N) 6. Route to Certification: Alternative or Traditional (Y/N) 7. Prior Educational Coursework (Y/N) 8. Length of Program (in weeks) 9. Prior Teaching Experienc e (Y/N) 10. Level of Education, Graduate (Y/N)

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126 Because prior research found all of these influences significant to explain the motivation to become a teacher (Hogan & Bullock, 2012; Richardson, Watt, & Karabenick, 2014; Spring, 2014), all of the predic tor variables were entered simultaneously into the regression model. The general equation model was as follows: (3 1) The description of the MR model notation is as follows: y : the dependent varia ble in the MR model (motivational factors) coefficient females); the standardized regression coefficient females); the standardized regression coefficient English); the standardized regression coefficient English); the standardized regression coefficient White); the standardized regression coefficient the standardized regression coefficient aving work experience in a non teaching job; the standardized regression coefficient to Traditional); the standardized regression coefficient : estimated slope in the MR model for having or not having prior education coursework; the standardized regression coefficient

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127 experience; the standardized regression coefficient not; the standardized regression coefficient teacher preparation pr ogram; the standardized regression coefficient Age of the teacher is an independent variable in the first MR model Gender is an independent variable in the second MR model, comparing teachers who identified as male to teachers who identified as female Gender is an independent variable in the third MR model, comparing Native language is an independent variable in the fourth MR model, comparing teachers who identified their native language as Spanish to teachers who identified their native language as English Native language is a n independent variable in the fifth MR model, comparing teachers who identified their native language as a language other than English to teachers who identified their native language as English Race/ethnicity is an independent v ariable in the sixth MR model, comparing teachers who identified their race/ethnicity as black to teachers who identified their race as white Native language is an independent variable in the seventh MR model, comparing teachers who identified their race/ethnicity as neither black nor white to teachers who identified their race as white Native language is an independent variable in the eighth MR model, comparing teachers who had or did not have non teaching work experience Native language is an independent variable in the ninth MR model, comparing teachers who had an Alternative or Traditional Route to Certification Native language is an independent variable in the tenth MR model, comparing teachers having or not having prior education coursework Native language is an independent variable in the eleventh MR model, comparing teachers having or not having prior teaching experience

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128 Native language is an independent variable in the fourth MR model, comparing teachers having or not ha ving a graduate degree Native language is an independent variable in the fourth MR model, comparing teachers based on the number of weeks in their teaching preparation program ei (sample) prediction er ror (or residual error) Chapter Summary My quantitative, retrospective exploratory study sought to explore the motivational factors scores of current Florida teachers for their reasons to choose teaching as a career. Additionally, teacher characteristics and teacher program characteristics were included and examined to estimate to what extent, if any, these variables were related to motivational factor Choice Scale and survey were used to guide the design, measureme nt and data analysis. A CFA was conducted to check if the FIT Choice model would appropriate to use in the present sample (i.e. if the FIT Choice Scale yields reliable and valid scores in the U.S. state of Florida context with in service teachers). T he re sults of the CFA indicated the standardized factor loadings for one item (Q67, 0.227) did not measure the satisfaction with choice motivational factor well and was removed from analysis. I provided strong evidence of validity for the inferences drawn from my data as well as strong evidence f or the reliability of my scores. I identified and defined variables to be measured (DVs motivational factors; IVs teacher characteristics and teacher program characteristics). Analytic procedures were chosen based on th e appropriateness and alignment with the data and research questions, and both descriptive and inferential statistics, specifically simultaneous MR, were used to analyze and describe the data.

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129 CHAPTER 4 RESULTS Using the FIT Choice Conceptual model and instrument, this study explored the initial motivational factors that influenced Florida K 12 public school teachers to choose a career in teaching and also measure the relationship, if any, between teacher characteristics and teacher preparation program c haracteristics on the motivational factor scores This design mechanism examined correlational rather than causational relationships among various factors and constructs in order to shed light as to what certain factors were most important to particular Fl orida K 12 public school teachers, categorized by their teacher characteristics and/or teacher program characteristics, as it relates to their choice of a career in teaching. The research questions that guided this study were: RQ 1 What were the motivati ons of Florida K 12 public school teachers to choose teaching as a career, as measured by the FIT Choice Scale? RQ 2 To what extent do teacher characteristics (age, race/ethnicity, gender, native language, prior non teaching work experience) and teacher p rogram characteristics route to certification, prior educational coursework, prior teaching experience, level of education, and length of teacher pre paration program) have a relationship with each motivational factor score? RQ 1: Motivations to Become a Te acher choose teaching, as measured by the FIT Choice Scale As discussed in Chapter 3, Confirmatory Factor Analysis (CFA) was conducted to measure the construct validity and reliability of each sub construct and the total survey, as well as test the internal structure of the scale. Due to the model fit, of the eighteen original motivational factor scores, thirteen were used in the analysis. Two of the thirteen were higher order factors, or measured by sub factors ( personal utility value

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130 and social utility value ) and eleven were first order factors, measured by individual items on the survey ( self perception s of teaching ability, intrinsic career value, fallback career, pri or teaching and learning experiences, social influences, expertise, difficulty, social status, salary, social dissuasion, and satisfaction with choice ). Results of the instrument were reported through descriptive statistics, which were measured with 58 ite ms on a Likert scale from 1 ( not at all important ) to 7 ( extremely important ). Mean scores and standard devi ations are reported in Table 4 1 Table 4 1. Descriptive Statistics: Mean Scores and Standard Deviations Motivational Factors M SD Influences to Become a Teacher Self perception s of Teaching Ability Intrinsic Career Value Fallback Career Personal Utility Value Social Utility Value Prior Teaching and Learning Experiences Social Influences Beliefs About Teaching Expertise Difficulty Social Status Sal ary Decision to Become a Teacher Social Dissuasion Satisfaction with Choice 6.00 5.54 1.95 3.62 5.82 5.66 3.13 5.21 5.06 3.75 2.34 4.15 5.73 1.07 1.30 1.19 1.35 1.24 1.48 1.81 1.46 1.69 1.52 1.45 1.74 1.45 Mean scores of participants ranged from t he lowest, for fallback career, M = 1.95 ( SD = 1.17) to highest, for self perception s of teaching ability M = 6.00 ( SD = 1.07). The results self perception s of teaching ability M = 6.00 ( SD = 1.07); social utility value M = 5.82 ( SD = 1.24); and prior teaching and learning experiences M = 5.66 ( SD = 1.48). These higher mean scores suggest that participants were more likely to be motivated to become a teacher bec ause: 1) they thought they had the qualities and capabilities of a good teacher, 2) they wanted to work

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131 with children and give back to society, and 3) they had positive prior teaching and learning experiences before choosing to become a teacher. The three lowest motivational factors were fallback career M = 1.95 ( SD = 1.19); salary M = 2.34 ( SD = 1.45); and social influences M = 3 .13 ( SD = 1.81). These lower mean scores suggest that participants were less likely to be motivated to become a teacher because: 1) they were unsure or did not get into their first career choice, 2) they thought teachers earned a good salary, and 3) they had family and/or friends who thought they should become a teacher. RQ 2: Multiple Regression Results Using simultaneous multiple regression, the second research question addressed the correlation between teacher characteristics and teacher program characteristics on each motivational factor score. In my study, thirteen (13) multiple regression models (Tables 2 14) were used to esti mate the prediction that ten (10) teacher and teacher preparation program characteristics had on a particular motivation factor, the outcome variable in this regression analysis. The ten (10) predictor variables were: 1. Race/Ethnicity (white, black, other) 2. G ender (female, male, other) 3. Native Language (English, Spanish, other) 4. Age 5. Prior Non Teaching Work Experience (Y/N) 6. Route to Certification: Alternative (Y/N) 7. Prior Educational Coursework (Y/N) 8. Length of Program (in weeks) 9. Prior Teaching Experience (Y/N) 10. Graduate Degree (Y/N) Because prior research found all of these influences significant to explain the motivation to become a teacher (Hogan & Bullock, 2012; Richardson, Watt, & Karabenick, 2014; Spring, 2014), all of the predictor variables were entered simultaneously into the regression model.

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132 The general equation model is as follows: (4 1) The description of the MR model notation is as follows: y : the dependent variable in the MR model (motivational factors) slope in the MR model for age; the standardized regression coefficie nt slope in the MR model for gender (comparing males to females); the standardized regression coefficient slope in the MR model for gender (comparing others to females); the standardized regre ssion coefficient slope in the MR model for native language (Spanish to English); the standardized regression coefficient slope in the MR model for native language (Others to English); the sta ndardized regression coefficient slope in the MR model for race/ethnicity (Black to White); the standardized regression coefficient slope in the MR model for race/ethnicity (Others to White); the standardized regression coefficient slope in the MR model for having or not having work experience in a non teaching job; the standardized regression coefficient slope in the MR model for route to certification (Alternative to Traditional); the standardized regression coefficient slope in the MR model for having or not having prior education coursework; the standardized regression coefficient slope in the MR model for the amount of prior teaching experience; the standardized regression coefficient

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133 slope in the MR model for holding a graduate degree or not; the standardized regression coeffi cient slope in the MR model for the number of weeks of teacher preparation program; the standardized regression coefficient Age of the teacher is an independent variable in the first MR model Gender is an independent variable in the second MR model, comparing teachers who identified as male to teachers who identified as female Gender is an independent variable in the third MR model, comparing teachers Native language is an independent variable in the fourth MR model, comparing teachers who identified their native language as Spanis h to teachers who identified their native language as English Native language is an independent variable in the fifth MR model, comparing teachers who identified their native language as a language other than English to teac hers who identified their native language as English Race/ethnicity is an independent variable in the sixth MR model, comparing teachers who identified their race/ethnicity as black to teachers who identified their race as white Native language is an independent variable in the seventh MR model, comparing teachers who identified their race/ethnicity as neither black or white to teachers who identified their race as white Native language is an independent variable in the eighth MR model, comparing teachers who had or did not have non teaching work experience Native language is an independen t variable in the ninth MR model, comparing teachers who had an Alternative or Traditional Route to Certification Native language is an independent variable in the tenth MR model, comparing teachers havi ng or not having prior education coursework Native language is an independent variable in the eleventh MR model, comparing teachers having or not having prior teaching experience Native language is an independent variable in the fourth MR model, comparing teachers having or not having a graduate degree

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134 Native language is an independent variable in the fourth MR model, comparing teachers based on the number of weeks in their teaching preparation program ei (sample) predic tion error (or residual error) To improve readability because of the numerous predictor variables (ten) and outcomes (thirteen motivation factor scor es), I reported only significant findings in the tables and text embedded in the narrative of this chapter, but full regression results of all predictor variables were reported at the end of the chapter. Full regression results are in Appendix E Additiona lly, to serve as a preview to the thirteen regression model results, I created two charts to provide a quick snapshot of the independent variables regarding both the type, as well as the extent (higher or lower motivational factor score) of the variables t hat were shown to have a statistically significant association with the dependent variables (motivational factors). Figure 4 1 reports not only when an independent variable (teacher or teacher preparation characteristic) had a statistically significant ass ociation with a particular motivational factor, but this chart also indicates by name what specific group of participants, on average, were more likely to be motivated to become a teacher due to a particular motivational factor. Figure 4 2 complements Fig ure 4 1 by providing the nature and direction of the slope (positive or negative). While all independent variables had a significant relationship with at least one of the dependent variables, the regression models did not explain much of the variance, with R 2 values ranging from 0.08 to 0.44, which speaks to the rich diversity and complexity of the data set. The section below Figure 4 2 will go into much great detail as to how and why.

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135 Figure 4 1. Variables and levels associated with higher motivation al scores.

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136 Figure 4 2. The positive and negative slopes of variables that had a statistically significant relationships

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137 Influential Factors The first area of focus on the FIT Choice Scale related to Influential Factors (Section B in Watt & Richar dson, 2006), which assessed the influential factors affecting respondents' choice of a career in teaching. This section contained 38 total items. Within the section, there were 5 first order factors and 2 higher order factors in this section. The five fir st order factors were self perception s of teaching ability qualities of a good teacher ) ; intrinsic career value (e.g. I have always wanted to be a teacher ) ; fallback career (e.g. I was not accepted into my first choice career ) ; prior teaching and learning experiences (e.g. I have had positive learning experiences ) ; and social influences (e.g. My family thinks I should become a teacher ). All 5 first order factors were each measured with 3 items for a total of 15 items. The first h igher order factor was personal utility value which contained 3 sub factors: job security (e.g. Teaching will offer a steady career path ); time for family ( Teaching hours will fit the responsibilities of having a family ) and job transferability (e.g. A teaching qualification is recognized everywhere ). The second higher order factor was social utility value, which contained 4 first order factors: shape the future of children/adolescents (e.g. Teaching will allow me to shape child and adolescent value s ), enhance social equity (e.g. Teaching will allow me to benefit the socially disadvantaged ), make social contribution (e.g. Teaching will allow me to provide a service to society ), and work with children/adolescents (e.g. I like working with childr en and adolescents ). All eleven first order factors, as well as the two higher order factors had separate regression models and results, thirteen total, which are reported below, in order.

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138 Self perception s of teaching a bility (Model 1) Table 4 2. Regre ssion Analysis: Statistically Significant Predictors of Self perception s of Teaching Ability Factors Sig. M a le_F emale .061 .000 Others_F emale .036 .025 R 2 = .008 ( F (13, 4,006) = 2.562, p < .002) A multiple linear regression was calculated to predict self perception s of teaching ability, based on ten teacher and teacher preparation program charact eristics (Model 1). Results of the regression analysis showed the overall model explained .08 % ( R 2 = .013 ) of the variance of self perception s of teaching ability among the respondents ( F (13, 4,006) = 2.562, p < .002 ). Self perception s of teaching ability is a motivational factor that measures the extent to which participants chose to become a teacher because they believed they had the qualities of a good teacher and/or they had good teaching skills and abilities (Richardson & Watt, 2006, p. 34). As prese nted in Table 4 2, only one independent variable, gender, was a significant predictor of self perception s of teaching ability, controlling for other factors (full results displayed in Appendix E ) The multiple regression analysis showed that teachers who i dentified as female had higher intrinsic career value motivational factor scores than teachers who identified as male as interpreted by the negative standardized regression coefficient ( ) score .061, and a statistically significant p value equal to zero. (This interpretation will be notated throughout the rest of the chapter as .094, p < .001 ). The two comparisons in the multiple regression analysis showed that females had higher self perception s of teaching ability motivational factor scores compared to both teachers who identified as male ( = .061, p =.0 00) and for teachers who identified their gender as other/chose not to respond ( = .036, p = .025). Due to the negative coef ficien ts, the results suggest that for teachers who identified as female their self perception of teaching ability was a higher motivational factor in their decision to

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139 become a teacher than it was for teachers who identified as male and others /preferred not to respond Intrinsic career value (Model 2) Table 4 3 Regression Analysis: Statistically Significant Predictors of Intrinsic Career Value Factors Sig. Male_Female .094 .000 Others_Female Non Teaching Work Experience (Y/N) Type of Certification: Alternative (Y/N) Prior Teaching Experience (Y/N) Graduate Degree (Y/N) Length of Program Prior to Teaching (in weeks) .033 .069 .086 .038 .048 .066 .037 .000 .000 .041 .003 .000 ( R 2 = .044, F (13, 4,000) = 14.183, p < .001) A multiple linear regression was fit to the data to predict intrinsic career value, based on ten teacher and teacher preparation program characteristics (Model 2). Results of th e regression analysis showed the overall model explained 4.4% ( R 2 = .044) of the variance of intrinsic career value among the respondents ( F (13, 4,000) = 14.183 p < .001) controlling for other factors Intrinsic career value is a motivational factor that measures the extent to which participants were influenced to become a teacher because they liked, had been interested in, or wanted to become a teacher before they chose teaching as their career (Richardson & Watt, 2006, p 34). As presented in Table 4 3 six of the ten independent variables were statistically significant predictors of intrinsic ca reer value (gender, non teaching work experience, type of certification, prior teaching experience, level of education, length of program prior to teaching), con trolling for other factors (full results displayed in Appendix E ). Gender was a statistically significant predictor for intrinsic career value, controlling for other factors. The multiple regression analysis showed that teachers who identified as female h ad lower intrinsic career value motivational factor scores than teachers who identified as male as

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140 interpreted by the negative standardized regression coefficient ( ) score .094, and a statistically significant p value equal to zero. (This interpretation will be notated throughout the rest of the chapter as .094, p < .00 1 ) Additionally, teachers who identified their gender as = .033, p = .037) also had, on average, lower intrinsic career motivational scores Due to the negative coefficients, the results suggest that for teachers who identify as female, intrinsic career value was a higher motivational factor in their decision t o become a teacher than it was for teachers who identified males, as well as other/prefer not to answer. Prior non teaching work experience Prior non teaching work experience was a statistically significant predictor of intrinsic career value, controllin g for other variables. The multiple regression analysis showed that teachers who had prior career experience in a non teaching field had higher scores than those teachers with no non teaching experience ( = .069, p < .001 ) controlling for other factors Due to the positive coefficient, the results suggest that for teachers who had had prior non teaching work experience before they chose to become a teacher, intrinsic career value was a lower motivational factor in their decision to become a teacher than i t was for teachers who had less non teaching related work experience prior to becoming a teacher. Certification Certification was a statistically significant predictor for intrinsic career value, controlling for other factors. The multiple regression ana lysis showed that teachers who completed an alternative route to certification (ARC) had higher scores than those teachers who did not complete an alternative route ( = .086. p < .001 ) controlling for other factors Due to the positive coefficient, the r esults indicate that for teachers who completed an ARC, intrinsic career value was a higher motivational factor in their decision to become a teacher than it was for teachers who completed a traditional route to certification (TRC).

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141 Prior teaching experie nce Prior teaching experience also was a statistically significant predictor of intrinsic career value, controlling for other variables. The multiple regression analysis showed that teachers who had prior teaching experience before becoming a teacher of r ecord had lower scores than those teachers no prior teaching experience ( = .038, p = .041). Due to the negative coefficient, the results suggest that for teachers who had prior teaching experience before becoming a teacher, intrinsic career value was a lower motivational factor in their decision to become a teacher than it was for teachers who did not have prior teaching experience prior to becoming a teacher. Education degree Education degree was a statistically significant predictor for intrinsic car eer value, controlling for other variables. Teachers who had completed a m or other graduate degree tended to have lower intrinsic career value motivational factor scores than teachers who had completed a graduate degree ( = .048, p = .003). Due to the negative coefficient, the results suggest that for teachers who did have a graduate degree intrinsic career value was a lower motivational factor in their decision to become a teacher than it was for teachers who did not h ave a graduate degree. Length of program Length of program prior to teaching also was a statistically significant predictor of intrinsic career value, controlling for other variables. The multiple regression analysis showed that teachers who had more wee ks of teacher program preparation prior to teaching had higher scores than those teachers with less teacher program preparation ( = .066, p < .001 ). Due to the positive coefficient, the results suggest that for teachers who had longer length of teacher preparation program in weeks, intrinsic career value was a higher motivational factor in their decision to become a teacher than it was for teachers who had shorter length of teacher preparation time in weeks.

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142 In summary, regarding the influence of intrinsic career value, these results indicate that the groups of people who were more influenced by this factor when choosing teaching as a career were: participants who identified as female, or alternatively certified, or who did not have a graduate degree, or did not have prior teaching experiences (as compared to their comparison groups). In addition, those teachers who had prior non tea ching work experience or who had long length of teacher preparation before becoming a teacher were also more influenced by the idea of teaching offering intrinsic career value, as compared to each comparison group. Fallback career (Model 3) Table 4 4 Reg ression Analysis: Statistically Significant Predictors of Fallback Career Factors Sig. Age Male_Female .044 .085 .007 .000 Others_Female Black_White Others_White Certification: Alternative (Y/N) Prior Teaching Experience (Y/N) Graduate Degree (Y/N) Length of Program Prior to Teaching (in weeks) .031 .032 .057 .082 .052 .035 .046 .050 .043 .001 .000 .006 .027 .004 ( R 2 = .041, F (13, 4,010) = 13.044, p < .001) A multiple linear regression was fit to the data to predict fallback career, based on ten teacher and teacher preparation program characteristics (Model 3). Results of the regression analysis showed the overall model explained 4.1% ( R 2 = .041) of the variance of fallback career among the respondents ( F (13, 4,010) = 13.044, p < .001) controlling for other factors Fallback career is a motivational factor that measures the extent to which participants chose to become teachers because they were unsure of the career they wanted, were not accepted into their first career choice, or because they chose teaching as a last resort career (Richardson & Watt, 2006, p. 34). As presente d in Table 4 4, seven of the ten independent variables were statistically significant predictors of intrinsic career value (age, gender, race/ethnicity, type of certification,

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143 prior teaching experience, level of education, length of program prior to teachi ng), controlling for other factors (full results displayed in Appendix E ). Age Age w as a statistically significant predictor of fallback career, controlling for other factors. The multiple regression analysis showed that teachers who were older tended to have lower fallback career motivational factor scores than teachers who were younger ( = .044, p =.007). Due to the negative coefficient, the results suggest that for teachers who were older, teaching as a fallback career was a lower motivational factor in their decision to become a teacher than it was for younger teachers. Gender Gende r was a statistically significant predictor of fallback career, controlling for other factors. The multiple regression analysis showed that teachers who identified as female had lower fallback career motivational factor scores than teachers who identified their gender as male ( = .085, p < .000), as well as other/prefer not to answer ( = .031, p = .050). Due to the positive coefficients, the results suggest that for teachers who identify as female, teaching as a fallback was a lower motivational factor in their decision to bec ome a teacher than it was for teachers who identified as male, as well as other/prefer not to answer. Race/ethnicity Race/ethnicity was a statistically significant predictor of fallback career. The multiple regression analysis showed that teachers who id entified as white had lower fallback career motivational factor scores than teachers who identified as black ( = .032, p = .043), as well as others, or teachers who identified their race as neither white nor black ( = .057, p = .001). Due to the positive coefficients, the results suggest that for teachers who identified as white, teaching as a fallback was a low er motivational factor in their decision to become a teacher than it was for teachers who identified themselves as black, as well as other ethnicity/race.

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144 Certification Certification was a statistically significant predictor for fallback career, controll ing for other variables. Teachers who completed an ARC tended to have lower fallback career motivational factor scores than teachers who did not complete an ARC ( = .082, p < .001 ). Due to the negative coefficient, the results indicate that for ARC teachers, teaching as a fallback career was a lower motivational factor in their decision to become a teacher than it was for TRC teachers. Prior teaching experience Prior teaching experience also was a statistically significant predictor of fallback career, controlling for other variables. The multiple regression analysis showed that teachers who had prior teaching experience before becoming a teacher of record had h igher scores than those teachers with no prior teaching experience ( = .052, p = .006). Due to the positive coefficient, the results indicate that for teachers who had had prior teaching work experience, fallback career was a higher motivational factor in their decision to become a teacher than it was for teachers who did not have prior teaching experience before becoming a teacher. Degree level Degree level was a statistically significant predictor for fallback career, controlling for other variables. Teachers who completed a m or other graduate degree tended to have higher fallback career motivational factor scores than teachers who had not completed a graduate degree ( = .035, p = .027). Due to the positive coefficient, the results suggest that for teachers with a m or other graduate degree teaching as a fallback career was a higher motivational factor in their decision to become a teacher than it was for teach ers without any type of graduate degree. Length of program Length of program prior to teaching also was a statistically significant predictor of fallback career, controlling for other variables. The multiple regression analysis showed that teachers who h ad more teacher program preparation in weeks had lower

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145 scores than those teachers with less teacher program preparation ( = .046, p = .004). Due to the negative coefficient, the results suggest that for teachers who had longer length of teacher preparation program in weeks, teaching as a fallback career was a lower motivational factor in their decision to become a teacher than it was for teachers who had shorter length of teacher preparation time in weeks. In summary, regarding the perceptions of teaching as a fallback career, these results indicate that the groups of people who were more influenced by this factor when cho osing teaching as a career were: participants who did not identify as female, or did not identify as white, or did not complete an ARC (as compared to their comparison groups). In addition, those teachers who were younger, or who had prior education course work, or who had a graduate degree, or who had shorter length of teacher preparation before becoming a teacher were also more influenced by the idea of teaching as a fallback career, as compared to each comparison group. Personal utility value (Model 4) Ta ble 4 5 Regression Analysis: Statistically Significant Predictors of Personal Utility Value Factors Sig. Age .058 .000 Prior Teaching Experience (Y/N) .074 .000 ( R 2 = .013 F (13, 3,947) = 3.853, p < .001) A multiple linear regression was fit to the data to predict personal utility value, based on ten teacher and teacher preparation program charact eristics (Model 4). Results of the regression analysis showed the overall model explained 1.3% ( R 2 = .013) of the variance of personal utility value among the respondents ( F (13, 3,947) = 3.853, p < .001) controlling for other factors Personal utility va lue is a higher order factor that measures the extent to which time for family,

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146 Richardson, 2007, p. 172). As presented in Table 4 5, two of the ten independent variables were statistically significant predictors of personal utility value, age and prior teaching experience (full results displayed in Appendix E ). Age Age was a statistically significant predictor of personal utility value, controlling for other f actors. The multiple regression analysis showed that teachers who were older tended to have lower personal utility value motivational factor scores than teachers who were younger ( = .058, p =.000). Due to the negative coefficient, the results suggest that for teachers who were older, personal utility value was a lower motivational factor in their decision to become a teacher than it was for younger teachers. Prior teaching exper ience Prior teaching experience also was a statistically significant predictor of personal utility value, controlling for other variables. The multiple regression analysis showed that teachers who had prior teaching experience before becoming a teacher of record had higher scores than those teachers with no prior teaching experience ( = .074, p < .001 ). Due to the positive coefficient, the results suggest that for teachers who had had prior teaching work experience, personal utility value was a higher motivational factor in their decision to become a teacher than it was for teachers w ho did not have prior teaching experience before becoming a teacher. Regarding the perceptions of personal utility value before making their choice to pursue teaching as a career, these results indicate that the groups of people who were more influenced by this factor when choosing teaching as a career were those with prior teaching experience or those teachers who were younger, as compared to each comparison group.

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147 Social utility value (Model 5) Table 4 6 Regression Analysis: Statistically Significant Predictors of Social Utility Value Factors Sig. Age Male_Female .058 .040 .000 .012 Others_Female Spanish_English Others_White .046 .039 .081 .004 .027 .000 ( R 2 = .020 F (13, 3,961) = 6.155, p < .001). A multiple linear regression was fit to the da ta to predict social utility value, based on ten teacher and teacher preparation program characteristics (Model 5). Results of the regression analysis showed the overall model explained 2% ( R 2 = .020) of the variance of intrinsic career value among the res pondents ( F (13, 3,961) = 6.155, p < .001) controlling for other factors Social utility value is a higher order factor that measures perceptions of teaching careers to shape the future of children, enhance social equity, make a social contribution, and s erve society by working with children (Watt & Richardson, 2007, p. 173). As presented in Table 4 6, four of the ten independent variables were statistically significant predictors of social utility value (age, gender, native language, race/ethnicity), cont rolling for other factors (full results displayed in Appendix E ). Age Age was a statistically significant predictor of social utility value, controlling for other factors. The multiple regression analysis showed that teachers who were older tended to hav e lower social utility value motivational factor scores than teachers who were younger ( = .058, p =.000). Due to the negative coefficient, the results suggest that for teachers who were older, social utility value was a lower motivational factor in thei r decision to become a teacher than it was for younger teachers. Gender Gender was also a statistically significant predictor of social utility value, controlling for other factors. The two comparisons in the multiple regression analysis showed

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148 that teac hers who identified as female had higher social utility value motivational factor scores than teachers who identified as male ( = .040, p =.012), as well as teachers who identified as other/prefer not to answer ( = .046, p = .004). Due to the negative coefficients, the results suggest that for females, their social utility value was a higher motivational factor in their decisi on to become a teacher than it was for teachers who identified as their gender as male and other/prefer not to answer. Native l anguage Native language was a statistically significant predictor of social utility value, but only when comparing teachers who were native English speakers or native Spanish speakers, controlling for other factors. The multiple regression analysis showed that native English speakers had lower social utility value motivational factor scores than native Spanish speakers ( = .039, p = .027), but not for teachers whose native language was neither English nor Spanish ( = .015, p = .349). Due to the positive coefficient, the results indicate that for native English speakers, social utility value was a lower motivational fact or in their decision to become a teacher than it was for native Spanish speakers. Race/ethnicity Race/ethnicity was a statistically significant predictor of social utility value, but only when comparing teachers who identified as white to teachers who id entified their race/ethnicity as other/prefer not to answer, controlling for other factors. The multiple regression analysis showed that teachers who identified as white had lower fallback career motivational factor scores than teachers who identified as o ther/preferred not to answer ( = .081, p < .001 ), but not for teachers who identified as black ( = .013, p = .418). Due to the positive coefficient, the results suggest that for teachers who identified as white, social utility value was a lower motivatio nal factor in their decision to become a teacher than it was for teachers who identified as other/prefer not to answer.

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149 Regarding the perceptions of social utility value before making their choice to pursue teaching as a career, these results indicate tha t the groups of people who were more influenced by this factor when choosing teaching as a career were: participants who identified as female, spoke Spanish as a first language, or did not identify as white or black (as compared to their comparison groups) In addition, those teachers who were younger were also more influenced by social utility value, as compared to each comparison group. Prior teaching and learning experience (Model 6) Table 4 7 Regression Analysis: Prior Teaching and Learning Experience s Factors Sig. Age Others_Female .048 .044 .003 .006 Prior Non Teaching Work Experience (Y/N) Prior Education Coursework (Y/N) .039 .039 .017 .017 ( R 2 = .010 F (13, 4,000) = 3.141, p < .001) A multiple linear regression was fit to the data to predict prio r teaching and learning experiences, based on ten teacher and teacher preparation program characteristics (Model 6). Results of the regression analysis showed the overall model explained 1% ( R 2 = .010) of the variance of prior teaching and learning among t he respondents ( F (13, 4,000) = 3.141, p < .001) controlling for other factors The motivational factor prior teaching and learning experiences relates to the positive teaching and learning experiences participants had before becoming a teacher, such as h aving inspirational teachers, good role models, and/or other positive learning experiences (Watt & Richardson, 2007, p. 174). As presented in Table 4 7, four of the ten independent variables were statistically significant predictors of prior teaching and l earning experiences (age, gender, prior not teaching work experience, and prior education coursework), controlling for other factors (full results displayed in Appendix E ).

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150 Age Age was a statistically significant predictor of prior teaching and learning experiences, controlling for other factors. The multiple regression analysis showed that teachers who were older tended to have lower prior teaching and learning experiences motivational factor scores than teachers who were younger ( = .048, p =.003). Du e to the negative coefficient, the results suggest that for teachers who were older having positive prior teaching and learning experiences was a lower motivational factor in their decision to become a teacher than it was for younger teachers. Gender Gen der was a statistically significant predictor of prior teaching and learning experiences, only when comparing females to others, not females to males, controlling for other factors. The multiple regression analysis showed that teachers who identified as fe male had higher prior teaching and learning motivational factor scores than teachers who identified their gender as other/prefer not to answer ( = .044, p = .006) but not males ( = .011, p = .506). Due to the negative coefficients, the results suggest t hat for teachers who identified as female, having prior positive teaching and learning experiences was a higher motivational factor in their decision to become a teacher than it was for teachers who identified as other/prefer not to answer. Prior non teac hing work experience Prior non teaching work experience also was a statistically significant predictor of prior teaching and learning experiences, controlling for other variables. The multiple regression analysis showed that teachers who had prior career experience in a non teaching field had higher prior teaching and learning scores than those teachers with no non teaching experience before becoming a teacher ( = .039, p = .017). Due to the positive coefficient, the results suggest that for teachers who had had prior non teaching work experience, prior positive teaching and learning experiences were a higher motivational factor in their

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151 decision to become a teacher than it was for teachers who did not have non teaching experiences before becoming a teache r. Prior education coursework Prior education coursework also was a statistically significant predictor of prior teaching and learning experiences, controlling for other variables. The multiple regression analysis showed that teachers who had prior educa tion coursework before becoming teachers had lower prior teaching and learning motivational factor scores than those teachers who did not have prior education coursework ( = .039, p = .017). Due to the negative coefficient, the results suggest that for t eachers who had had prior educational coursework, prior positive experiences with teaching and learning was a lower motivational factor in their decision to become a teacher than it was for teachers who did not have educational coursework prior to becoming a teacher. Regarding the influence of positive prior teaching and learning experiences before making their choice to pursue teaching as a career, these results indicate that the groups of people who were more influenced by this factor when choosing teach ing as a career were: participants who were younger, or identified their gender as female (but only when compared to In addition, participants who had prior non teaching work experience, or did not have prior education course work were also more influenced by positive prior teaching and learning experiences, as compared to each comparison group. Social Influence (Model 7) Table 4 8 Regression Analysis: Statistically Significant Predictors of Social Influences Factors Sig. Age Males_Female .044 .033 .007 .040 Prior Teaching Experience (Y/N) Graduate Degree (Y/N) .054 .045 .004 .005 ( R 2 = .012 F (13, 4,003) = 3.847, p < .001)

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152 A multiple linear regression was fit to the data to predict social influences, based on ten teacher and teacher preparation program characteristics (Model 7). Results of the regression analysis showed the overall model explained 1.2% ( R 2 = .012) of the variance of social influences among the respondents ( F (13, 4,003) = 3.847, p < .001) cont rolling for other factors The motivational factor social influences measures the influences that participants had from family members and friends encouraging them to become a teacher (Watt & Richardson, 2007, p. 174). As presented in Table 4 8, four of th e ten independent variables were statistically significant predictors of social influences (age, gender, prior teaching experience, and level of education), controlling for other factors (full results displayed in Appendix E ). Age Age was a statistically significant predictor of social influences, controlling for other factors. The multiple regression analysis showed that teachers who were older tended to have lower social influences motivational factor scores than teachers who were younger ( = .044, p =.007). Due to the negative coefficient, the results suggest that for teachers who were older, social influences were a lower motivational factor in their decision to become a teacher than it was for younger teachers. Gender Gender was a stat istically significant predictor of social influences, only when comparing females to males, not females to others, and controlling for other factors. The multiple regression analysis showed that females had lower social influences motivational factor score s than males ( = 0.33, p = .040), but not for teachers who identified their gender as other/prefer not to answer ( = .021, p = .182). Due to the positive coefficients, the results suggest that for teachers who identified as female, social influences was a lower motiv ational factor in their decision to become a teacher than it was for teachers who identified as male.

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153 Prior teaching experience Prior teaching experience was a statistically significant predictor of social influences, controlling for other variables. The multiple regression analysis showed that teachers who had prior teaching experience before becoming a teacher of record had lower social influences scores than those teachers with no prior teaching experience ( = .054, p = .004). Due to the positive coefficient, the results suggest that for teachers who had had prior teaching experience before becoming a teacher, social influences was a lower motivational factor in their decision to become a teacher than it was for teachers who did not have prior teaching experience before becoming a teacher. Degree level Degree level was a statistically significant predictor for social influences, controlling for other variables. Teachers who completed a or other gra duate degree tended to have lower social influences motivational factor scores than teachers who had not completed a graduate degree ( = .045, p = .005). Due to the negative coefficient, the results suggest that for teachers with a m or other graduate degree social influences was a lower motivational factor in their decision to become a teacher than it was for teachers without any type of graduate degree. Regarding the perceptions of social influences before making their choice to pursue teaching as a career, these results indicate that the groups of people who were more influenced by this factor when choosing teaching as a care er were: participants who were male, or had prior teaching work experience, or who did not hold a graduate degree (as compared to their comparison groups). In addition, those teachers who were younger were also more influenced by social influences, as comp ared to each comparison group. Beliefs About Teaching The second section of the FIT Choice Scale is Beliefs about Teaching. It contains 4 first order factors. Expertise (e.g. Do you think teaching requires high level of expert knowledge? )

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154 and difficulty/ high demand (e.g. Do you think teachers have a heavy workload? ) are measured with 3 items each. Social status is measured by 6 items (e.g. Do you think teachers are perceived as professionals? and Do you think teaching is a well respected career? ) a nd Salary is measured by 2 items (e.g. Do you think teachers earn a good salary? ). There are 14 total Expertise (Model 8) Table 4 9 Regression Analysis: Statistically Significant Predictors of Ex pertise Factors Sig. Male_Female Spanish_English .038 .044 .018 .014 Others_English Graduate Degree (Y/N) .038 .043 .019 .009 ( R 2 = .010 F (13, 3,993) = 3.052, p < .001) A multiple linear regression was fit to the data to predict expertise, based on ten teacher an d teacher preparation program characteristics (Model 8). Results of the regression analysis showed the overall model explained 1% ( R 2 = .010) of the variance of expertise among the respondents ( F (13, 3,993) = 3.052, p < .001). The motivational factor expe rtise measures knowledge (Watt & Richardson, 2007, p. 174). As presented in Table 4 9, three of the ten independent variables were statistically significant pre dictors of expertise (gender, native language, level of education), controlling for other factors (full results displayed in Appendix E ). Gender Gender was a statistically significant predictor of expertise as a motivational factor when comparing females to males, but not females to others, and controlling for other factors. The multiple regression analysis showed that teachers who identified as female had lower expertise motivational factor scores than teachers who identified as male ( = 0.38, p = .018), but not teachers who identified their gender as other/prefer to answer ( = 0.01, p = .950).

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155 Due to the positive coefficients, the results suggest that for teachers who identified as female, expertise was a lower motivational factor in their decision to become a teacher than it was for teachers who identified as male. Native l anguage Native language was a statistically significant predictor of expertise, controlling for other factors. The two comparisons in the multiple regression ana lysis showed that native English speakers had lower expertise motivational factor scores than both native Spanish speakers ( = .044, p = .014), as well as native speakers of other languages ( = .038, p = .019). Due to the positive coefficients, the results suggest that for native English speakers, expertise was a lower motivational factor in their decision to become a teacher than it was for native speakers of all other languages. Degree level Degree level was another statistically significant predictor for expertise, controlling for other variables. Teachers who completed a or other graduate degree tended to have h igher expertise motivational factor scores than teachers who had not completed a graduate degree ( = .043, p = .009). Due to the positive coefficient, the results suggest that for teachers with a or other graduate degree expertise was a higher motivational factor in their decision to become a teacher than it was for teachers without any type of graduate degree. Regarding the perceptions of that teaching requires a high level of expertise before making their choice to pursue teaching as a career, these results indicate that the groups of people who were more influenced by this factor when choo sing teaching as a career were: participants who identified as either male or other/prefer not to answer; or participants whose native language was Spanish or other non English language, who held a graduate degree (as compared to their comparison groups).

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156 Difficulty (Model 9) Table 4 10 Regression Analysis: Statistically Significant Predictors of Difficulty Factors Sig. Age Others_White .114 .053 .000 .003 ( R 2 = .022 F (13, 3,996) = 6.886, p < .001) A multiple linear regression fit to the data to pr edict difficulty, based on ten teacher and teacher preparation program characteristics (Model 9). Results of the regression analysis showed the overall model explained 2.2% ( R 2 = .022) of the variance of difficulty among the respondents ( F (13, 3,996) = 6. 886, p beliefs that teaching requires hard work or is taxing (Watt & Richardson, 2007, p. 174). As presented in Table 4 10, two of the ten independent variables were statistically significa nt predictors of difficulty (age, race/ethnicity), controlling for other factors (full results displayed in Appendix E ). Age Age was a statistically significant predictor of difficulty, controlling for other factors. The multiple regression analysis show ed that teachers who were older tended to have lower difficulty motivational factor scores than teachers who were younger ( = .114, p =.000). Due to the negative coefficient, the results suggest that for teachers who were older, difficulty was a lower motivational factor in their decision to become a teacher than it was for younger teachers. Race/ethnicity Race/ethnicity w as a statistically significant predictor of difficulty, but only when comparing whites to others, not whites to blacks, and controlling for other factors. The multiple regression analysis showed that teachers who identified as white had lower difficulty mo tivational factor scores than teachers who identified as others ( = .053, p = .003), but not for teachers who identified as black ( = .017, p = .274). Due to the positive coefficients, the results suggest that for teachers who identified as white, difficulty was a lower motivational

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157 factor in their decision to become a teacher than it was for teachers who identified themselves as neither white nor black. Regarding the perceptions of the difficulty of teaching before making their choice to pursue teaching as a career, these results indicate that the groups of people wh o were more influenced by this factor when choosing teaching as a career were: participants who identified as black or other/prefer not to answer (as compared to their comparison groups). In addition, those teachers who were younger were also more influenc ed by the difficulty of teaching as a career, as compared to each comparison group. Social Status (Model 10) Table 4 1 1 Regression Analysis: Statistically Significant Predictors of Social Status Factors Sig. Prior Education Coursework (Y/N) .052 .001 Prior Teaching Experience (Y/N) Graduate Degree (Y/N) .040 .034 .035 .035 ( R 2 = .007 F (13, 3,972) = 2.099, p < .012) A multiple linear regression was fit to the data to predict social status, based on ten teacher and teacher preparation program charact eristics (Model 10). Results of the regression analysis showed the overall model explained 0.7% ( R 2 = .007) of the variance of social status among the respondents ( F (13, 3,972) = 2.099, p < .012). The motivational factor social status measures participant society (Watt & Richardson, 2007, p. 174). As presented in Table 4 11, three of the ten independent variables were statistically significant predictors of social status (prior educati on coursework, prior teaching experience, level of education), controlling for other factors (full results displayed in Appendix E ). Prior education coursework Prior education coursework was a statistically significant predictor of social status, control ling for other variables. The multiple regression analysis

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158 showed that teachers who had prior education coursework had higher scores than those teachers with no prior education coursework ( = .052, p = .001). Due to the positive coefficient, the results s uggest that for teachers who had had prior educational coursework, social status was a higher motivational factor in their decision to become a teacher than it was for teachers who did not have educational coursework prior to becoming a teacher. Prior teac hing experience Prior teaching experience also was a statistically significant predictor of social status, controlling for other variables. The multiple regression analysis showed that teachers who had prior teaching experience before becoming a teacher o f record had higher scores than those teachers with no prior teaching experience ( = .040, p = .035). Due to the positive coefficient, the results suggest that for teachers who had had prior teaching work experience, social status was a higher motivationa l factor in their decision to become a teacher than it was for teachers who did not have prior teaching experience prior to becoming a teacher. Degree level Degree level was a statistically significant predictor for social status, controlling for other v ariables. Teachers who completed a or other graduate degree tended to have lower social status motivational factor scores than teachers who had not completed a graduate degree ( = .034, p = .035). Due to the negative coefficient, the results suggest that for teachers with a or other graduate degree social status was a lower motivational factor in their decision to become a teacher than it was for teachers without any type of graduate degree. Regarding the perceptions of social status before making their choice to pursue teaching as a career, these results indicate that the groups of people who were more influenced by this factor when choosing teaching as a career were: participants who had teaching work experience,

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159 prior education coursework, or did not have a graduate degree (as compared to their comparison groups). Salary (Model 11) Table 4 1 2 Regression Analysis: Statistically Significant Predictors of Salary Facto rs Sig. Age .076 .000 Prior Teaching Experience (Y/N) Length of Program Prior to Teaching (Y/N) .045 .032 .017 .050 ( R 2 = .013 F (13, 4,011) = 3.958, p < .001) A multiple linear regression was fit to the data to predict salary, based on ten teach er and teacher preparation program characteristics (Model 11). Results of the regression analysis showed the overall model explained 1.3% ( R 2 = .013) of the variance of salary among the respondents ( F (13, 4,011) = 3.958, p < .001). The motivational factor salary measures paid profession (Watt & Richardson, 2007, p. 174). As presented in Table 4 12, three of the ten independent variables were statistically significant predictors of salary (age, prior tea ching experience, length of program prior to teaching), controlling for other factors (full results displayed in Appendix E ). Age Age was a statistically significant predictor of salary, controlling for other factors. The multiple regression analysis sho wed that teachers who were older tended to have higher s alary motivational factor scores than teachers who were younger ( = .076, p =.000). Due to the positive coefficient, the results suggest that for teachers who were older, salary was a higher motivational factor in their decision to become a teacher than it was for younger teachers. Prior teaching experience Prior tea ching experience also was a statistically significant predictor of salary, controlling for other variables. The multiple regression analysis showed that teachers who had prior teaching experience before becoming a teacher of record had higher scores than t hose teachers with no prior teaching experience ( = .045, p = .017). Due to the

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160 positive coefficient, the results suggest that for teachers who had had prior teaching work experience, salary was a higher motivational factor in their decision to become a teacher than it was for teachers who did not have prior teaching experience prior to becoming a teacher. Length of program Length of program prior to teaching also was a statistically significant predictor of salary. The multiple regression analysis showed that teachers who had more teacher program prep aration in weeks had lower salary motivational factor scores than those teachers with less teacher program preparation in weeks ( = .032, p = .050). Due to the negative coefficient, the results suggest that for teachers who had longer length of teacher preparation program in weeks, salary was a lower motivational factor in their decision to become a teacher than it was for teacher s who had shorter length of teacher preparation time in weeks. Regarding the perceptions of salary before making their choice to pursue teaching as a career, these results indicate that the groups of people who were more influenced by this factor when cho osing teaching as a career were those who had prior teaching experience, or those teachers who were older, or had shorter length of teacher preparation before becoming a teacher were also more influenced by salary, as compared to each comparison group. Dec ision t o Become a Teacher The third section of the FIT Choice Scale is Your Decision to Become a Teacher It has 2 first order factors, social dissuasion (e.g. Did others tell you teaching was not a good career choice ? ), measured by 3 items and satisfact ion with choice ( How satisfied are you with your choice of becoming a teacher ? ) measured by 2 items each. 3 This section assesses experiences of social dissuasion along with satisfaction with the choice of a teaching career. 3 As noted in Chapter 3, question Q67 was omitted from the survey du e to poor model fit.

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161 Social Dissuasion (Model 12) Table 4 1 3 Regression Analysis: Statistically Significant Predictors of Social Dissuasion Factors Sig. Age .178 .000 Male_Female Spainsh_English Others_White Work Experience Non Teach (Y/N) Certification: Alternative (Y/N) Prior Education Coursew ork (Y/N) Graduate Degree (Y/N) Length of Program Prior to Teaching (in weeks) .058 .048 .077 .080 .055 .052 .050 .034 .000 .006 .000 .000 .003 .001 .002 .030 ( R 2 = .059 F (13, 4,000) = 19.216, p < .001) A multiple linear regression was fit to the da ta to predict social dissuasion, based on ten teacher and teacher preparation program characteristics (Model 12). Results of the regression analysis showed the overall model explained 5.9% ( R 2 = .059) of the variance of social dissuasion among the responde nts ( F (13, 4,000) = 19.216, p < .001). The motivational factor social dissuasion measures the influence that others had on participants discouraging them from choosing teaching as a career (Watt & Richardson, 2007, p. 174). As presented in Table 4 13, nine of the ten independent variables were statistically significant predictors of social dissuasion (age, gender, native language, race/ethnicity, prior non teaching work experience, route to certification, prior education coursework, level of educ ation, length of program prior to teaching), controlling for other factors. The independent variable that was not statistically significant was prior teaching experience ( = 010, p =.582) (full results displayed in Appendix E ). Age Age was a statistica lly significant predictor of social dissuasion, controlling for other factors. The multiple regression analysis showed that teachers who were older tended to have lower social dissuasion factor scores than teachers who were younger ( = .178, p =.000).

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162 Du e to the negative coefficient, the results suggest that for teachers who were older, social dissuasion was a lower motivational factor in their decision to become a teacher than it was for younger teachers. Gender Gender was a statistically significant pr edictor of social dissuasion for females and males, but not for females and others, and controlling for other factors. The comparison in the multiple regression analysis showed that teachers who identified as female had lower social dissuasion motivational factor scores than teachers who identified as male ( = .058, p =.000), but not others ( = .004, p =.797). Due to the positive coefficient, the results suggest that for teachers who identified as female, social dissuasion was a lower motivational factor in their decision to become a teacher than it was for teachers who identified as male. Native l anguage Native language was a statistically significant predictor of social dissuasion for English compared to Spanish, controlling for other factors. The mul tiple regression analysis showed that native English speakers had lower social dissuasion factor scores than native Spanish speakers ( = .048, p = .006). Due to the positive coefficients, the results suggest that for native English speakers, social dissuasion was a lower motivational factor in their decision to become a teacher than it was for native Spanish speakers. Race/ethnicity R ace/ethnicity was a statistically significant predictor of social dissuasion, but only when comparing whites to others, not whites to blacks, and controlling for other factors. The multiple regression analysis showed that teachers who identified as white h ad lower social dissuasion motivational factor scores than teachers who identified as others ( = .077, p < .001 ), but not for teachers who identified as black ( = .002, p = .895). Due to the positive coefficients, the results suggest that for teachers who identified as white, social

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163 dissuasion was a lower motivational factor in their decision to become a teacher than it was for teachers who identified themselves as neither white nor black. Prior non teaching work experience Prior non teaching work experience also was a statistically significant predictor of social dissuasion as a motivating fact or, controlling for other variables. The multiple regression analysis showed that teachers who had prior career experience in a non teaching field had lower social dissuasion motivational factor scores than those teachers with no non teaching experience ( = .080, p =.000). Due to the negative coefficient, the results suggest that for teachers who had had prior non teaching work experience, social dissuasion was a lower motivational factor in their decision to become a teacher than it was for teachers who had no non teaching experience prior to becoming a teacher. Certification Certification was a statistically significant predictor for social dissuasion, controlling for other variables. Teachers who completed an alternative route to certification tended to have lower social dissuasion motivational factor scores than teachers who did not complete an ARC ( = .055, p = .003). Due to the negative coefficient, the results suggest social dissuasion was a lower motivational factor for ARC teachers in their decision to become a teacher than it was for TRC teachers. Prior education coursework Prior education c oursework also was a statistically significant predictor of social dissuasion, controlling for other variables. The multiple regression analysis showed that teachers who had prior education coursework had lower social dissuasion scores than those teachers with no prior education coursework ( = .052, p = .001). Due to the negative coefficient, the results suggest that for teachers who had had prior educational coursework, social dissuasion was a lower motivational factor in their decision to become a

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164 teacher than it was for teachers who did not have educational coursework prior to becoming a teacher. Degree level Degree level was a statistically significant predictor for social dissuasion, controlling for other variables. Teachers who completed a m or other graduate degree tended to have higher social dissuasion motivational factor scores than teachers who had not completed a graduate degree ( = .050, p = .002). Due to the positive coefficient, the results suggest that for teachers with a m or other graduate degree social dissuasion was a higher motivational factor in their decision to become a teacher than it was for teachers without any type of graduate degree. Length of program Length of program prior to teaching also was a statistically significant predictor of social dissuasion, controlling for other factors. The multiple regression analysis showed that teachers who had more teac her program preparation in weeks had lower social dissuasion scores than those teachers with less teacher program preparation in weeks ( = .034, p = .030). Due to the negative coefficient, the results suggest that for teachers who had longer length of teacher preparation program in weeks before becoming a teacher, social dissuasion was a lower motivational factor in their decision to bec ome a teacher than it was for teachers who had shorter length of teacher preparation time in weeks. Regarding the influence of social dissuasion before making their choice to pursue teaching as a career, these results indicate that the groups of people wh o were more influenced by this factor when choosing teaching as a career were: participants who identified their gender as male, spoke Spanish as their native language, did not identify as white or black, had no non teaching work experience, no prior educa tion coursework, or who were traditionally certified (as compared to their comparison groups). In addition, those teachers who were younger, or had

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165 shorter length of teacher preparation before becoming a teacher were also more influenced by social dissuasi on, as compared to each comparison group. Satisfaction with Choice (Model 13) Table 4 1 4 Regression Analysis: Statistically Significant Predictors of Satisfaction with Choice Factors Sig. Age .135 .000 Others_Female Non Teaching Work Experience (Y/N) .032 .035 .046 .033 ( R 2 = .021 F (13, 3,998) = 6.439, p < .001) A multiple linear regression was fit to the data to predict satisfaction with choice, based on ten teacher and teach er preparation program characteristics (Model 13). Results of the regression analysis showed the overall model explained 2.1% ( R 2 = .021) of the variance of satisfaction with choice among the respondents ( F (13, 3.998) = 6.439, p < .001). The motivational pursue teaching as a career (Watt & Richardson, 2007, p. 174). As presented in Table 4 14, three of the ten independent variables were statistically significant predicto rs of satisfaction with choice (age, gender, prior non teaching work experience), controlling for other factors (full results displayed in Appendix E ). Age Age was a statistically significant predictor of satisfaction with choice, controlling for other f actors. The multiple regression analysis showed that teachers who were older tended to have higher satisfaction with choice motivational factor scores than teachers who were younger ( = .135, p =.000). Due to the positive coefficient, the results suggest that for teachers who were older, their satisfaction with choice was a higher motivational factor in their decision to become a teacher than it was for younger teachers. Gender Gend er was a statistically significant predictor of satisfaction with choice, but only when comparing females to others, not females to males, and controlling for other factors.

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166 The comparison in the multiple regression analysis showed that teachers who identi fied females had higher satisfaction with choice motivational factor scores than teachers who identified as other/preferred not to answer ( = .032, p =.046), but not for males ( = .024, p =.136). Due to the negative coefficient, the results suggest that satisfaction with choice was a higher motivational factor for teachers who identified as female than for teachers who identified as other Prior non teaching work experience Prior non teaching work experience also was a statistically significant predictor of satisfaction with choice, controlling for other variables. The multiple regression analysis showed that teachers who had prior caree r experience in a non teaching field had higher satisfaction with choice scores than those teachers with no non teaching experience ( = .035, p =.033). Due to the positive coefficient, the results suggest that for teachers who had had prior non teaching work experience, satisfaction with choice was a higher motivational factor in their decision to become a teacher than it was for teach ers who had no non teaching experience prior to becoming a teacher. Regarding the perceptions of satisfaction of choice with teaching as a career, these results indicate that the groups of people who were more influenced by this factor when choosing teachi ng as a career were: teachers who identified their gender as female (when compared to in a non teaching capacity. In addition, those teachers who were younger w ere also more influenced by being satisfied with their teaching career choice, as compared to each comparison group. Chapter Summary This chapter provided the results to the two research questions that guided my study: 1) What were the motivations of Flor ida teachers to choose teaching, as measured by the FIT

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167 Choice Scale ? and 2) To what extent do teacher characteristics (age, race/ethnicity, gender, native language, prior non teaching work experience) and teacher program characteristics route to certifica tion, prior educational coursework, prior teaching experience, level of education, and length of teacher pre paration program) have a relationship on each motivational factor score? To answer the first research question, descriptive statistics measures of c entral tendency and variability were used to measure and report scores. Mean scores and standard deviations were used to interpret the overall average score of each of the thirteen motivational factors for all participants. To answer the second research qu estion, inferential statistics, specifically simultaneous multiple regression, were used to explain the prediction of the independent variables (teacher characteristics and teacher preparation program characteristics) on the dependent variables (motivation al factors). This analysis shed light as to which factors were more likely to be associated with teachers to elect a career in teaching. In general, there were many independent variables (teacher and teacher program characteristics) that had statis tically significant relationships with The extent to which variables displayed statistical significance ranged from two to nine statistically significant relationships with a particular motivational factor. In the next chapter I discussed these findings in connection to the literature and provide implications for future research.

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168 CHAPTER 5 DISCUSSION AND IMPLICATIONS The purpose of my quantitative exploratory study was to use a vetted framework (the FIT Cho ice Conceptual model) and subsequent scale to explore the initial motivations of Florida public school teachers to elect teaching as a career, as well as estimate the extent to which teacher characteristics and teacher preparation program characteristics h ad a relationship with particular motivational factors. I endeavored to uncover what influences, beliefs, and values were most important to Florida teachers in choosing a career in teaching, categorized into certain typologies (e.g. gender, race, type of c ertification) based on their personal characteristics and/or the teacher preparation program in which they participated. This chapter begins with a discussion of the results related to my two research questions, and then progresses to provide implications for future research. The two research questions that guided my study were: RQ 1 What were the motivations of Florida K 12 public school teachers to choose teaching as a career, as measured by the FIT Choice scale? RQ 2 To what extent do teacher character istics (age, race/ethnicity, gender, native language, prior non teaching work experience) and teacher program characteristics (route to certification, prior educational coursework, prior teaching experience, level of education, and length of teacher prepar ation program) have a relationship with each motivational factor score? Discussion There have been more than two dozen research studies encompassing over twenty samples using Watt and Richardson's FIT Choice scale (Akar, 2012; Berger & D'Ascoli, 2012; Fok kens al., 2012; Knig & Rothland, 2012; Leech & Haug, 2015; Leech, Haug, & Bianco, 2015; Leech, Haug, & Nimer, 2015; Leech, Haug, Ridgewell, & Ruben, 2018; Lin et al., 2012; Richardson &

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169 Watt, 2010; Watt et al., 2012; Watt & Richardson, 2007; Watt, Richardson, & Smith, 2017; Yu & Bieger, 2013). This framework has been widely used in a range of cultural settings and different samples, and results from the FIT Choice surveys ha ve reported high validity and reliability scores examining the motivations of preservice teachers in multiple countries and settings, such as Australia, Austria, China, Croatia, Estonia, Germany, Indonesia, the Netherlands, Norway, the Republic of Ireland, Switzerland, and the United States (Akar, 2012; Berger & D'Ascoli, 2012; Brandmo & Nesje, 2017; Fokkens Bruinsma & Canrinus, 2012; Gratatcs, Lpez Gmez, Nocito, and Sastre, 2017; Hennessy & Lynch, 2017; Heinz, Keane, & Kilin et al., 2012; Knig & Rothland, 2012; Lin et al., 2012; Richardson & Watt, 2010; Watt & Richardson, 2007; Taimalu, Luik, & Tht, 2017; Watt et al., 2012; Yu & Bieger, 2013). However, the FIT Choice scale has only been used with in service teachers within the U.S. in two different sample populations, s pecifically in a Western state in the United States (Leech & Haug, 2015; Leech, Haug, & Nimer, 2015; Leech, Haug, Ridgewell, & Ruben, 2018). The current FIT Choice studies typically fall into three main categories: 1) studies that focus on understanding the reliability, validity, and over all fit of the model 2) studies that preservice and 3) studies that focus on understanding teacher Richardson, 2012, p. 189). The majority of the above studies align with the first category (Akar, 2012; Berger & D'Asc oli, 2012; Fokkens Bruinsma & Canrinus, 2012; Hennessy & Lynch, 2017; Kilin et al., 2012; Leech & Haug, 2015; Leech, Haug & Bianco, 2015; Lin et al., 2012; Richardson & Watt, 2010; Watt et al., 2012; Yu & Bieger, 2013). A few studies, including

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170 al. (2012) and Knig & Rothland (2012), fall into the latter category where additional factors are incorporated into the FIT Choice model for an expanded viewpoint of their particular sample. It is in this vein that my study aligns. My study was both exp loratory and retrospective in nature. It was exploratory because there was little empirically based evidence on which to build this particular study in this sp ecific context, and I examined correlational relationships among important constructs in teacher motivations to form the basis for future research. Therefore, the inferences drawn are limited to the particular context of my study and current Florida K 12 public school teachers ; as such, findings should not be generalized to other populations or sample s Furthermore, comparing my results to other FIT Choice studies or other studies examining teacher motivations should be made with caution, as there are numerous ways that my study differs conceptually and methodologically. Conceptually, while I used Watt design and theoretical framework, my study is unique in several ways. I not only measured motivations of in service teachers in the U.S., specifically in Florida, but my sample also contained a substa ntial number of teachers who were certified through alternative teacher certification programs, as opposed to more traditional routes. To date, almost all of the samples within the FIT Choice literature omit teachers who have been alternatively certified. Of the three existing studies that examined the motivations of in service teachers, the two sample populations within those studies were from a very homogeneous Western state (Leech & Haug, 2015; Leech, Haug, & Nimer, 2015; Leech, Haug, Ridgewell, & Ruben, 2018). Neither those studies, nor any other previous FIT Choice studies have had sample populations that reflected the level of diversity that is represented in the state of Florida. Furthermore, all previous FIT Choice studies

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171 have had relatively small s ample sizes, ranging from less than 100 to just over 2,000. Rather than focusing on specific sets of teachers across a small population, I sought input from the entire public school teaching populations of Florida, resulting in the largest data set yet rec orded using the FIT Choice scale ( n only sample within the FIT Choice literature that has included both in service teachers who completed a university based, or traditional route to certi fication (TRC), as well as an alternative route to certification (ARC). However, there were a very low percentage of participants in n = 4). That being said, only a very small percentag e of teachers within that larger state teacher population were alternatively certified; therefore, their data set was somewhat reflective of the larger teacher population demographics of that state. Conversely, almost a third of Florida teachers have been certified through one of the 433 Florida based ARC programs (Jacobs, 2017), and 27% of the respondents in my sample were alternatively certified. Methodologically, while I did employ survey research methods, the majority of the studies have been measureme nt studies, critically examining the validity and reliability of the FIT Choice scale and its appropriateness to be used across different samples. Although it was necessary to establish the appropriateness of using the FIT Choice framework and scale within my sample through CFA and other measurement analyses, inferences regarding the internal structure and validity of the FIT Choice with current teachers in Florida or the U.S. should also be made with caution. My study does provide some evidence related to the factor structure by which I measured and interpreted the motivational factors of Florida teachers to choose a career in teaching. However, it would be necessary for me conduct further research in order to provide stronger evidence as to the extent to w hich the factor structure is similar, or different, to the

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172 underlying latent constructs represented by the factors. Therefore, this study is largely exploratory but has implications for future research studies, which will be discussed toward the latter par t of this chapter. Discussion of the Findings In the sections below, I will be addressing each Research Question in turn. Findings related to Research Question 1 shed light on certain motivational factors that were, on average, most important to Florida pu blic school K 12 teachers within my sample to choose a career in teaching. Findings related to Research Question 2 indicate to what extent certain teacher characteristics and/or teacher program characteristics had a relationship with certain motivational f actors. Findings R elated to RQ1 To answer Research Quest ion 1, descriptive statistics were used to measure, analyze and interpret the motivational factor variable scores to the 58 Likert scale items (from 1, not at all important to 7, extremely ) for each participant on the survey. I measured th e total overall mean scores and standard deviations to examine Florida K motivations for choosing teaching as a career, their perceptions of the profession, and their satisfaction with care er choice. Results are displayed below in Table 5 1. Table 5 1. Descriptive Statistics: Mean Scores and Standard Deviations Motivational Factors M SD Influences to Become a Teacher Self perception s of Teaching Ability Intrinsic Career Value Fallback Car eer Personal Utility Value Social Utility Value Prior Teaching and Learning Experiences Social Influences Beliefs About Teaching Expertise Difficulty 6.00 5.54 1.95 3.62 5.82 5.66 3.13 5.21 5.06 1.07 1.30 1.19 1.35 1.24 1.48 1.81 1.46 1.69

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173 Table 5 1. Continued Motivational Factors M SD Social Status Salary Decision to Become a Teacher Social Dissuasion Satisfaction with Choice 3.75 2.34 4.15 5.73 1.52 1.45 1.74 1.45 As noted in Chapter 4, mean scores of participants ranged from the lowest, for fallback career, M = 1.95 ( SD = 1.17) to highest, for self perception s of teaching ability M = 6.00 ( SD = 1.07). The were self perception s of teaching abil ity M = 6.00, ( SD = 1.07); social utility value M = 5.82 ( SD = 1.24); and prior teaching and learning experiences M = 5.66 ( SD = 1.48). These higher mean scores suggest that participants were more likely to be motivated to become a teacher because: 1) they thought they had the qualities and capabilities of a good teacher, 2) they wanted to work with children and give back to society, and 3) they had positive prior teaching and learning experiences before choosing to become a teacher. The three lowest motiv ational factors were fallback career M = 1.95 ( SD = 1.19); salary M = 2.34 ( SD = 1.45); and social influences M = 3.13 ( SD = 1.81). These lower mean scores suggest that participants were less likely to be motivated to become a teacher because: 1) they were unsure or did not get into their first career choice, 2) they thought teachers earned a good salary, and 3) they had family and/or friends who thought they should become a teacher. Comparative s tudies: M otivational scores for in service teachers in the U .S. As mentioned previously, there has been very limited research conducted on in service teachers within the U.S. Therefore, the closest studies to which to compare my study are to Leech and Haug (2015) and Leech, Haug, Ridgewell, and Ruben (in press ). Ho wever, these comparisons should be made with restraint, as they were both conducted in a Western state that is very

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174 homogeneous, had sample sizes that were small ( between 150 and 250 participants ), and had different scopes, purposes, methods, and analyses. Leech and Haug (2015) examined the motivations of in service teachers across seven school districts in a Western state, and findings from that data set were reported in two different publications. Leech and Haug (2015) first examined the construct validit y and reliability of the FIT Choice scale and compared their results of the in service U.S. teachers to that of the preservice Leech and Haug (2015) discovered the questions fit the factors differently than previo us studies with preservice teachers. This finding led the authors to believe that the in service teachers and preservice teachers were from different populations and viewed their motivation to teach in different ways. The second research study completed by Leech, Haug, Ridgewell, & R uben (in press ) also examined the motivations of teachers within that same Western state. However, they collected and analyzed data from three school districts that had reported high conflict between teachers and their reflectiv e school boards, one from a district with a history of long term, high conflict and two districts with short term, medium conflict districts. The participants in that study had low motivational scores with regard to job security social status and salary but higher scores when it came to difficulty and expertise Not surprisingly Leech Haug, Ridgewell, & Ruben (in press ) reported that the longer the turmoil and instability in the district continued, the lower the motivation scores tended to be for these teachers regarding the positive aspects of their profession. The mean scores and standard deviations across these two studies and my study are provided in Table 5 2 below.

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175 Table 5 2. Mean Scores and Standard Deviations of In Service Teachers within th e U.S. Leech & Haug (2015) Leech, Haug, Ridgewell & Ruben (2018) Ridgewell (2018) Motivational Factors M SD M SD M SD Influences to Become a Teacher Self Perceptions of Teaching Ability 6.06 0.89 5.97 1.03 6.00 1.07 Intrinsic Career Value 5.88 1.05 5.70 1.22 5.54 1.31 Fallback Career 1.63 0.84 1.51 0.82 1.95 1.19 Job Security* 4.27 1.44 4.10 1.33 4.39 1.71 Time for Family* 2.82 1.30 2.53 1.09 3.35 1.64 Job Transferability* 3.08 1.42 2.78 1.33 3.15 1.59 Personal Utility Value 3.62 1.35 Shape Future of Children and Adults** 5.83 1.05 5.73 1.21 6.05 1.25 Enhance Social Equity** 5.12 1.53 4.77 1.59 5.15 1.76 Make Social Contribution** 5.95 1.07 5.97 1.11 6.05 1.26 Work with Children and Adolescents** 5.81 1.22 5.44 1.34 6.05 1.26 Social Utility Value 5.82 1.25 Prior Teaching and Learning Experiences 5.37 1.46 4.97 1.22 5.66 1.49 Social Influences 3.07 1.73 2.72 1.45 3.13 1.82 Beliefs About Teaching Expertise 5.55 1.63 5.90 0.90 5.21 1.46 Difficulty 6.03 1.70 6.66 0.45 5.06 1.70 Social Status 3.09 1.40 2.97 1.00 3.75 1.52 Salary 2.45 1.42 2.35 1.15 2.34 1.45 Decision to Become a Teacher Social Dissuasion 3.30 1.67 3.89 1.72 4.15 1.75 Satisfaction with Choice 5.42 1.79 5.76 1.06 5.73 1.46 Motivation factors were collapsed into Personal Utility Value *Motivation factors were collapsed into Social Utility Value When examining the results of my study against these two other in service studies, many of the results were very similar. However, there were a few noticeab le differences. For example, the

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176 motivational factor score for time for family was hig her in my study ( M 3.35, SD = 1.64 ) than it was in the two other in service teacher studies ( M = 2.82/1.30; SD = 2.53/1.09, respectively); however, given the factor stru cture within the scale I used to measure motivational factor scores, I collapsed time for family into the higher order factor, personal utility value ( M = 3.62; SD = 1.35). The motivational factor scores for social status were higher in my study ( M = 3.75; SD = 1.52 vs M = 3.09, SD = 1.40; M = 2.97, SD = 1.00, respectively). The motivational factor scores for difficulty were an entire point lower in my study ( M = 5.06, SD = 1.70 vs M = 6.03, SD = 1.70; M = 6.66, SD = 0.45, respectively). While the nuances i n scores of demographics and teacher characteristics in my study will be discussed with regard to Research Question 2 below, overall, the motivational factor scores indicated that the majority of in service teachers across all three samples believed teachi ng required a high level of expertise, was difficult, had low social status, low pay, and yet scores indicated participants felt teaching had both personal career value and societal value. Finally, the majority of the in service teachers believed they very much had the capabilities to be a good teacher and were ultimately satisfied with their choice. My study brings additional value to the field in that it is only the third study of its kind measuring in Choi ce scale, sampling a population previously unexplored. By studying a previously uncharted territory with the FIT Choice Scale, my study has the potential to contribute to the ever growing international investigation of motivational theory in teacher educat ion. However, the unique attributes of my study are also a double edged sword in that because my study is exploratory in nature, it is limited by this distinctiveness, thus requires the need for future research to replicate and expand my findings. In addit ion, due to its uniqueness, any direct comparisons with prior studies should be made with caution.

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177 Findings Related to RQ2 In addition to contributing to the literature by sampling a new subset of educators previously unexplored, I also wanted (Watt & Richardson, 2012, p. 189). Simply stated, I sought to better understand what influences, beliefs, and values were most important to Florida K 12 public school teachers in choosing a career in teaching, categorized into certain typologies (e.g. gender, race, type of certification) based on their personal characteristics and/or the teacher preparation program in which they participated as measured in tandem with the FIT Choice Scale. In order to achieve th is goal, (i.e. answer the second research question), I used simultaneous multiple regression to estimate which of these independent variables had a relationship with particular motivational factor scores. Results indicate that all ten independent variables (teacher and teacher program characteristics) had at least two statistically significant relationships across all thirteen dependent variables (motivational factors), indicating there are myriad elements at play related to the motivations of Florida K 12 public school teachers to elect a career in teaching. The table below provides a list of the motivational factors and the number of times there was a statistically significant relationship with each motivational factor score

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178 Motivational Factor Number of Times There was a Statistically Significant Relationship Fallback Career 9 Social Dissuasion 9 Intrinsic Career 7 Social Utility Value 5 Prior T & L Experience 4 Social Influences 4 Expertise 4 Difficulty: 3 Social Status 3 Salary 3 Satisfa ction with Choice 3 Personal Utility Value 2 Teaching Ability 2 Figure 5 1 Motivational Factors and the corresponding number of statistically significant relationship with each motivational factor score: While my f irst research question assesses the e xtent to which the FIT Choice scale can appropriately estimate the initial motivations of Florida public school teachers to elect teaching as a career, the second research question assesses whether and to what extent specific groups may differ in how they important to distinguish the difference between, on one hand, having a similar factor structure Within my data set, there was much variability among the different motivational factors; however the variance was small. W hile all independent variables had a significant relationship with at least one of the dependent variables, the regression models did not explain much of the variance, with R 2 values ranging from 0.08 % to 0.44 % which speaks to the rich diversity and complexity of the data set. Below are the most substantive results in my data set with regard to how teacher and teach er program characteri stics had a statistically significant relationship with the thirteen motivational factors used in my analysis.

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179 Teacher c haracteristics fallacies is the notion that a person learns only the particular thing [he/she] is studying at the p. 49). American public school children come away from school learning lessons about power, gender, class, race, inequalities, and cultural values that are not always explicitly stated in value s, motivations, and aspirations (Apple, 2013; Ahwee, et al.; 2103; Carter & Welner, 2013; Eisner, 1994; Hinchey; 2010; Spring, 2014). People are lifelo ng learners, and the walls of the schoolhouse are permeable to external societal factors. The section below discusses the extent to which Florida K relationship with partic ular motivational factor scores. This information garnered by the FIT Choice scale sheds light on an area that has had limited exploration or examination as one delves into the reasons why these in service teachers elected teaching as a career in the first place. Of the ten independent variables analyzed, five related to teacher characteristics and demographics: age, gender, race/ethnicity, native language, and prior non teaching work experience. Of these, two substantive findings related to gender and race /ethnicity and their relationship with the thirteen motivational factor scores are further explored below. Gender One interesting finding of my study was that gender had a statistically significant e comparisons should be made with caution, unlike many previous studies using the FIT Choice scales, in which males and females tended to be more, or less, motivated by similar factors (Watt, Richardson, & Smith, 2017) the results in my study suggest gende rs differed in both the number of and extent to which factors were more likely to motivate them to become a teacher. My study indicated not only were there

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180 many statistical differences in the mean scores between genders, there were also noticeable differen ces in the direction of the relationship of the observed variables; in other words, there hree motivational factors self perception s of teaching ability, intrinsic career value, and social utility value females, on average, were likely to have higher scores than males and others (indicating they were motivated by that factor), while males tende d to have higher scores than females (but not necessarily others) for the following four factors: fallback career, social influences, expertise, and social dissuasion. In one instance regarding fallback career necessarily generalizable, this finding aligns with previous research as to how gender is an important part of s, beliefs, and world perspectives (Ahwee et al., 2013; Apple, 2013; Brandmo & Nesje, 2017; Jackson, 2013; Nash, 2005). Given that, it was not unanticipated t o find significant differences of the motivational factor scores among genders for fallback caree r Researchers have suggested that students quickly learn about gender roles in school, even if distinctions regarding gender roles may not appear on the official curriculum (Apple, 2013; Ahwee et al. 2013; Spring, 2014). For example, because the majority of teachers are female, students may be more likely to connect to the idea that teaching is a female occupation, along with nursing, clerical work, and domestic service jobs (Apple, 2013; Ahwee, et al.; 2103; Nash, 2005; Spring, 2014). Conversely, females are less likely to be encouraged join or exposed to the fields of science, engineerin g, math, and technology (King, Pringle, Cordero, & Ridgewell in press ; Terzian 2006). Students may never be explicitly instructed to believe this, but students have obse rved who are most often recruited

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181 for these positions (through pamphlets, the media, or job fairs, etc.) and who actually fills the openings. Students could also notice that males dominate the powerful or administrative positions, and with specific regard to education, could observe that males tend to teach in secondary and higher education institutions. Thus, students are being taught what to think about gender, specifically as it relates to teaching, through what is modeled before them. Because teaching i s often considered a feminized field with low prestige, the perception Ahwee et al., 2013 ; Apple, 2013). As Wood (2007) particularly given the hubris of some educational researchers and policy makers and the experiences (p. 729). Unfortunately, the negative stigma that still has lingered in the minds of many Americans. Additionally, Apple (2013) examined how the profession of teaching has shifted from intellectual to more mechanical work, and people who possess power in education (e.g. male administrators) do not always value the knowledge, skills, and dispositions necessary to be an effective teacher. Differences in gender between males (18.5%) and females (79.8%) Fi ndings from my study indicate that males, on average, may believe the opposite: they do believe that teaching requires a high level of specialized and technical knowledge, as indicated by the higher scores of males in expertise. With regard to the high sco res of social influences and social dissuasion, findings indicate males, on average, were more likely to be influenced in their decision by how their friends, family and peers either supported or discouraged them to become teachers than their female counte rparts. It is also important to note that when compared to females, males had,

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182 on average, statistically significant higher motivational scores in social dissuasion. Therefore, males might be more hesitant to become a teacher, which is further supported by their indication that teaching was a fallback career through their statistically significantly higher scores for that variable. If males were more likely to believe teaching requires a high level of expertise, is difficult (as did all participants, M = 5. 06; SD = 1.70), has low compensation, and also are dissuaded against teaching, it seems plausible that there would be a statistically significant difference as it relates to teaching being a fallback career. Females, on the other hand, not surprisingly had higher motivational scores for intrinsic career value and self perceptions of teaching ability than those who identified as male. On average, females may have believed they would be good teachers. Mann (1841) stated over 175 comparably better teachers for young children than males, cannot admit of a doubt. Their manners are more mild and gentle, and hence more in consonance with become teachers, the stereotype prevailed, and subsequently the notion that if females were capable, they should be willing to become teachers. In my study, on average, those who identified as female were more likely to choose teaching as a career than people wh o identified as either males or others for the following reasons: the influence of their positive self perceived teaching ability, their interest for and long term desire to become a teacher, the ability to work with children, to decrease social inequities and to give back to society. On average, people who identified as female were more likely than people who identified as other/preferred not to answer to be influenced to become a teacher due to positive prior teaching and learning experiences. However, t here was not a statistically

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183 significant different relationship between females and males for prior teaching and learning experiences, suggesting that their average scores were more similar in nature. influence is more geared toward the and domestic values (Nash, 2005 ). While females in their roles as former and current patriarchal societal norms limit the value (Wa tt, Richardson & Devos, 2012, p. 189). Given that, it is not surprising that females would have higher scores with regard to social utility value because females are often viewed stereotypically as people who are supposed to work with children, give back t o society, and that females have better embedded teaching abilitie s. n s, 2011, p. 107). Therefore, it is not surprising that, on average, many females felt they had the capabilities to become a teacher and therefore made the decision that they should be a teacher from an early age due to societal norms (henc e the higher motivational scores). Differences in gender between people who identified as other/preferred not to answer 1.7% and females (79.8%) While fallback career scores were low across my sample, people who identified as other or chose not to identi fy their gender had statistically significant higher

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184 scores for this factor than females. Given the dark history of how the LGTBQ teacher community has been treated in Florida (Graves, 2014), as well as the historical and present conservative political cli mate in Florida, it is not surprising that people who identify as other might have been hesitant to become a teacher and thus viewed teaching as a fallback career. As Schneider and Dimito (2010) note: In addition to all the usual considerations [regarding career choices], LGBT people must assess whether their sexual orientation plays a role when there might be an otherwise good fit. Specifically, it is the impact of discrimination real, perceived, or anticipated that is purported to play an extra role in t he ca reer development of LGBT people (p. 1358) On a N ational level, while teachers work closely with students on a daily basis, teachers (Lugg, 2006), and subsequ ently are often discriminated and marginalized, either explicitly or implicitly This negative stigma has permeated through to schools, causing additional challenges and barriers to teachers of the LGTBQ community (Lugg, 2006). Race Another important findi ng, especially for researchers interested in race and ethnicity, is that despite the diversity represented in the teacher population in Florida, there were few statistically significant differences across races and ethnicities There were only four motivat ional factors in which there was a statically significant difference in scores: fallback career, social utility value, difficulty, and social dissuasion This indicated that within my sample, teachers of all colors and creeds, on average, tended to align c losely with regard to what motivated them to become a teacher. Nevertheless, when compared to their white counterparts, teachers who identified as a teacher of color (non black), multiracial, or having multiple ethnicities, including Asian, Haitian, Native American etc., on average, were more likely to have higher social utility value scores than

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185 their comparison group (white teachers). These teachers on average were more influenced to become a teacher because they highly valued giving back to the community working for the benefit of the disadvantaged, and inspiring the next generation for success as major driving factors behind pursuing teaching as a career. However, this finding did not indicate that other teachers in the sample did not share these same b eliefs, as the mean score for the total sample of Florida K 12 public school teachers for social utility value was 5.82. It only signifies that, on average multiracial teachers did have statistically higher scores as compared to teachers who identified as white. On average, teachers of color (but not black) were also more likely to be dissuaded from teaching than their comparison group (white), and on average, perceived teaching as a difficult career. However all teachers of color in my sample (i.e. both bl ack and multiracial teachers) tended to report higher motivation scores in choosing teaching as a fallback career than their white counterparts. Results revealed that for teachers of color (non black), they were, on average more likely to perceive that te aching was emotionally draining, had a heavy workload, and were encouraged to purse another career other than teaching, as compared to their white counterparts. Results also indicated that for all teachers of color, they were likely to be unsure of the car eer they wanted or chose teaching as a fallback career, as compared to white teachers. One astonishing finding, especially for researchers, educators, and other community stakeholders, is that overall motivational scores across races and ethnicities repres ented in my sample are quite similar, with the exception of four motivational factors. Despite the compounding challenges often faced by teachers of color, as opposed to their white counterparts Kumashiro, 2009 ; Ladson Billings, 2003; Siddle Walker 1996; 2011), there were, on average, still few statistically significant differences among

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186 the motivational factor scores across all races and ethni c ities of Florida K 12 public school teachers in this sample. Results from my study indicate that the influences, beliefs, and expectations of in service Florida K 12 public school teachers in my sample had when electing teaching as a career may be more similar amongst races and ethnicities than what has been previously sug gested from the 2004) or the assumption that teachers of all races and ethnicities in my sample may not have similar motivations, to the same degree, which calls i nto question some aspects within existing 2017; Kumashiro, 2009 ; Ladson Billings, 2003; Siddle Walker 1996; 2011). While there may be nuances in the manner in wh ich these motivations manifested as they influenced these teachers to choose a career in teaching, with the exception of four motivational factors, on average the motivations did not vary in the degree to which they affected these teachers. However, t here are myriad factors contributing to the motivations of in service Florida K 12 public school teachers, as evidenced by the depth and breadth of statistically significant differences reported beyond race and ethnicities, as well as taking into account the fa ctors that were not considered in my model. As noted previously, there are no similar existing studies either using the FIT Choice Scale or otherwise examining race/ethnicity and teacher motivations to which to compare mine, and future research studies usi ng the FIT Choice are needed to have a better understanding of the Program Characteristics Not only are ay in which following section delves deeper into the teacher preparation program characteristics that had a

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187 strategically significant relationship with part Due to the variances in the number and degree, my results reinforce the notio n that the context in which people l earn is just as important as what they learn, specifically with regard to what may have impacted their mo tivation to become a teacher. This information garnered from the use of the FIT Choice scale in tandem with variables that measured the routes, coursework, prior teaching experiences, and program length of participants exposes previously unchartered territ ories as to what motivated in service Florida public school teachers to make the decision to become a teacher in the first place. Certification R oute Another added value of my study is that it uncovered that certification as measured by the binary yes/no item, only had a statistically significant relationship with three motivational factor scores: intrinsic career value, fallback career, and social dissuasion. As stated previously, there is a great diversity of teacher preparation progr ams in the state of Florida (433 ), yet there was little diversity with reference to the variance within the motivational factor scores for those teachers who reported whether or not they completed an ARC. On average, people who indicated they completed an ARC tended to have h igher intrinsic career value scores, as compared to their comparison group. In other words, those who completed an ARC may have been even more likely to have had a greater interest to become a teacher than those who did not complete an ARC. These results d o call into question some of the negative stereotypes of teachers who are alternatively certified, specifically TFA teachers, who have questioned the motives of why alternatively certified teache rs join the field (Hartman, 2013 ; Imig & Imig, 2008; Ravitch, 2010). For example, teachers who complete an ARC, typically liberal do

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188 (Hartman, 2013, p. 2 ). Moreover, because people who completed ARCs, on average, tended to have lower fallback career scores, as compared to people who completed an TRC, my results she d new light on previous literature that suggests that the majority of ARC teachers enter teaching for self serving purposes, such as a stepping stone into a more lucrative career, or studies that suggest that teachers who complete ARCs do not really want to teach otherwise they eted a more traditional route ( Butler, T.E., 2014 ; Hartman, 2013 ; Kee, 2012; Ravitch, 2010). Finally, alternatively certified teachers also had lower social dissuasion scores, as compared to teachers who indicated they were traditionally certified, indicat ing that on average, teachers who completed and ARC were less discouraged to become teachers than their traditionally certified peers. To my knowledge, no previous study using the FIT Choice scale has either measured or discussed this distinction. This fin ding raised new queries, such as what were the motivations for people who had not yet decided to become teachers, but were considering it as a career choice through traditional or alternative routes. Because my study was exploratory in nature, my results w ould have to be replicated and further expanded. Other Teacher Preparation Program Characteristics While route to certification, as measured through the yes/no binary question was a statistically significant predictor for only three motivational factors, there were many more statistically significant differences within the other independent variables that typically characterize teacher preparation programs prior education coursework, prior teaching experience, graduate degree, and length of program These variables had statistically significant effects on ten of the thirteen motivational factors: intrinsic career value, fallback career, personal utility value, prior teaching and learning experiences, social influences, expertise, difficulty, social status, salary, and social dissuasion Not only were there many statistically significant

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189 differences in the mean scores, but there were noticeable differences in the direction of the relationship with the observed variables. Thus, highlighting which motivational factors had a greater influence on participants who did, or did not have prior education coursework, prior teaching experience, a graduate degree as well as statistically significant differences of participants who had longer or shorter teacher preparatio n programs (all typical characteristics of ARCs). Within these four independent variables alone, there were 20 individual statistically significant differences on participants motivational scores, showing the great discrepancies amongst the characteristics of alternative programs, much more than the simple yes/no response question alone (only 3 statistically significant motivational factors), as discussed above. These results highlight the need for further research into exploring the beliefs, influences, an d motivations for why people elected teaching as a career based on the characteristics of different routes to certification, rather than relying on two or three condensed categories (e.g. alternative/traditional, or ITPs, EPIs, and PDCPs) to which to compa re and assess. As there is currently no other study by which to compare my results, future research should also further delineate their classifications of teacher program characteristics using the FIT Choice Scale with Florida teachers. Implications for F uture Research My stu dy contributed to the both educational research and practice in several ways. It has the potential to contribute to the knowledge base on teacher motivational theory research and provides implications for practice and direction for fur ther research to better understand a) Florida K characteristics and teacher program characteristics have a relationship with particular motivations and c) how that understanding can be used to broaden, improve, and sustain teacher recruitment and retention efforts. The contributions of this study are multi layered due to the

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190 depth and breadth of the dataset and the unique findings that were garnered from the data. R esearchers can leve rage the voices and feedback of teachers to inform efforts focused on improving the recruitment, preparation, and retention of teachers, which ultimately could increase teacher quality and diversity, as well as better educational learning experiences for F examine Florida K minor adjustments to the scale, to contribute to the larger body of both FIT Choice research and overall educational research. The unique setting, population, and context in which this study was conducted illuminates how the FIT Cho ice Scale can support educational researchers and practitioners to improve teacher recruitment, p reparation, and retention in an area that had yet to be explore d. However, there is the need for sustained research using motivational research to be conducted over a long term time frame. The goals and intentions of doing so align with the Institute of E Exploratory Research, under Research Type 2 that the proposed research will generate important knowledge to inform the development, im p. 16 ). Further steps as laid out in the IES/NSF (2013) framework are to expand thi s exploratory study to the Research Type 3 stage, Design and Development Research where the tool may continue to be altered and improved upon to lead to better results. Pending the results of Research Stage 3, I Impact Research where analyses s hould be elaborated upon to provide deeper insights conn ecting to th e underlying theory ( Inst itute of Education Sciences & National Science Foundation 2013, p. 9).

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191 Implication and Directions for Future Research 1 : Why did Florida K 12 Public School Teachers Want to Become a Teacher in the First Place? This analysis of t he influences, beliefs, perceptions, motivations, and perceptions shows that on average, current (2016 2017) Florida public school K 12 teachers chose to become a teacher due to a) high levels of interest, b) high levels of confidence in their abilities an d possessing the qualities of a good teacher, and c) high levels of commitment of giving back to the community and society, enhancing social equities, and positively impacting the next generation. The analysis and subsequent findings of teacher motivations in my study included both the overall motivational factors of the sample, as well as delved more deeply into specific her preparation program characteristic s. These findings suggest that at the teacher recr uitment stage (for entrance into teacher preparation programs or quick hire directly into the classroom) it is essential that teacher education programs and school districts target a range of values and motivational factors that together impact the decisio n to enter teaching as a career. Additionally in Florida, because new teachers and teacher candidates are entering the p rofessional pipeline through 433 routes brimming with enthusiasm and excitement, it is imperative that both teacher education programs, and induction programs in districts capitalize on this enthusiasm and nurture these new teachers and teacher candidates. To continue forward positively, it is also necessary that new teachers and teacher candidates be provided with structured time, space, strategies, and supports to come to terms with their own beliefs about challenging demands of the teacher workplace. Recommendations for teacher preparation programs and induction programs are to build on greater variety of skills and experiences, or

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192 e and skills, these teachers and teacher candidates will have a better understanding of the context in which they will be teaching and participate in meaningful critical reflection to help improve their practice (Dewey, 1988; Hoffman Kipp, Artiles, & Lopez Torres, 2003; Rodgers, 2002; Schn, descr iption in particular, require the teacher to confront the complexity of students and their learning, of themselves and their teaching, their subject matter, and the contexts in which all eed to call into question their assumptions regarding what beliefs, values, and aspirations diverse teachers and teacher candidates bring with them in order to ensure that these teachers not only are able to maintain their initial motivations and aspiratio ns for joining the field, but also improve their development and sustained interest and commitment to the field. To continue forward positively, attempts should be made to help the new teachers achieve the goals they held when first entering the field and On the other end of the spectrum, another area in need of further research is to study i ndividuals who either never joined the teaching pr ofession, or have left teach ing. Results from my, or other FIT Choice studies, cannot speak to what motivated someone to not choose teaching as a career. Due to this significant gap in the literature, r esearch exploring what has deterred people from choosing teaching is greatly neede d, given the characteristics of the field.

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193 Much more research is needed expanding the FIT Choice Scale to a broader population as well as inquiring as to why the general population of Florida or even other states, may not have been motivated for teaching Implication and Directions for Future Research 2: The Paradox of Being Dissuaded, yet Satisfied One major problem introduced in Chapter 1 is the current (and future) shortage of high quality teachers in general and perceived low interest and prestige of joining the teaching field. One finding which may have implications for teacher practitioners, preparation programs, and education stakeholders is the dichotomy between the high levels of dissuasion against pursuing teaching as a career and the ultimate h igh satisfaction with the career choice. On average, all participants reported low social influences scores ( M = 3.13, SD = 1.82), high social dissuasion scores ( M = 4.15, SD = 1.75), but even higher satisfaction scores ( M = 5.73, SD = 1.46). This finding indicates not only were participants less likely to be positively influenced by their social sphere to become a teacher, but adversely, participants were more likely to be dissuaded by others to become a teacher. Nevertheless, on average, participants were satisfied with their career results in their first series of Australian studies indicating preservice teachers in Australia experienced higher levels of social dissuasion, rather than high levels of positive social influence when choosing teaching as a career. Another potential implication for practice, for both teacher preparation programs and K 12 employment institutions, is to explicitly acknowledge that thei r teacher candidates or employee candidat es were most likely discouraged rather than encouraged from choosing teaching as a career; thus both institutions should make programmatic changes -in recruiting teacher candidates or through induction programs for new hires -to provide more support

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194 ignore those doubts all together. Furthermore, during onboarding or orientation, programs and schools should actively pursue the evidence uncovered in my data set, reporting that even despite high levels of dissuasion from friends and family, teachers who remained in the field were highly satisfied with their choice of career. Future research opportunities exploring this dichotomy could focus on the main sources of this dissuasion. Better understanding the negative influencers on potential future teachers would allow teacher education programs and the education field in general to create focused materials revealing the benefits and opportunities afforded by joining the teaching field. Additionally, understanding when this dissuasion begins could also be important to help stakeholders begin providing positive information at an ear ly stage. This proactive approach has proved effective in other aspects of education, including encouraging middle school aged African American girls to remain interested in STEM fields as this was the age at which dissuasion was heaviest for these girls (King, Pringle, Cordero, & Ridgewell in press ). Implication and Directions for Future Research 3 : Biases in Hiring Teacher Candidates In addition to addressing the overall teacher shortage, another dilemma introduced in Chapter 1 was the need for more hig h quality and diverse teachers. To overcome these shortfalls, 12 school system and tailor recruitment strategies to appeal to a wider audience. In order to encourage t eacher candidates from currently underrepresented groups to consider a career in teaching, both teacher preparation programs and K 12 employment institutions should increase and strengthen their relationship with schools and community who are focused on su pporting such groups (Boland & Keane, 2011; Heinz 2011). This intentional involvement could provide

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195 more exposure and increase the interest to people who are less represented in the current teaching population to the potential benefits of becoming a teach er and supporting more focused collaboration between teacher education providers and community groups supporting disadvantaged pupils could potentially even encourage more students from currently underrepresented groups to consider teaching as a career (Bo land & Keane, 2011). My findings suggest that across many teacher characteristics and demographics, participants had high interest and motivations for joining the field. While motivating more and better qualified and diverse candidates to choose a career i n teaching is a major factor, another area of future resea rch is to examine other reasons that expand upon motivations as to why the teaching pool continues to remain so homogeneous. The issue is complex, and there is no panacea for improving teacher diver sity and quality; however, one main area that could be contributing to this dilemma is that there is not necessarily only a problem with recruiting diverse teachers into teaching, but also a problem with hiring them; thus, they are not represented due to t 2017; Hudson, 2017 ; Siddle Walker, 2011) Due to the complexity of this problem, it is necessary that educational researchers, practitioners, and stakeholders take into con sideration the systemic and cultural biases that permeate schools and society when problematizing what may be causing the lack of representation of certain population groups in the teaching force. Implications for both research and practice are to consider other barriers in the education system and society at large that may be causing the diversification and the improvement of the teaching pool to remain stagnant. Two often negatively viewed groups of people in the teaching profession are those who complete d alternative routes to certification and people of color, specifically African American males.

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196 Contradictory to the commonly held viewpoint that each of these groups of people may possess a lack of desire to become teachers, my findings suggest the opposi te. My findings challenge many the assumption of who does and does not perceive teaching as an attractive career, based on certification route alone. As noted previously, participants in my sample who indicated they completed an ARC, on average, tended to have longer term or higher interest in becoming a teacher than teachers who completed a TRC. Alternatively certified teachers in my sample also reported they were more confident and had a higher desire to choose a career in teaching, as indicated by their higher intrinsic career value and lower fallback career scores, respectively. These findings in m y study refute pr evious literature which often suggest Butler, T.E., 2014 ; Hartman, 2013 ; Kee, 2012; Rav itch, 2010). Implications for future research and practice are to problematize the classification of how teacher candidates are prepared for the field as either ARC or TRC, or specifically in Florida as Initial Tea cher Preparation Programs Educator Prepar ation Institutes and Professional Developmen t Certification Programs Both teacher preparation programs, principals, and school district administrators may need to re evaluate how teachers are hired on the hiring practices for teachers based on the evaluation of the preparation program e g. education coursework, prior teaching experience, length of program, etc.), r ather than merely comparing routes to certification by name only. More specifically, additional research should be conducted exploring principals administrators certified, as they are typically the individuals who are making the decisions to hire and retain teachers (Bartholomew, Bullock, & Nadelson, 2018).

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197 As with the comparison between ARCs and TRCs, there were few statistically significant motivational factor differences ac (2017) argue that the absence of African American males and other people of color in the teaching profession not only due to the lack of motivation of becoming a teacher; instead it is also due to many people in society who do not acknowledge or understand the extent to which everyday practices in schools often comply with or contribute to racism, sexism, classism, heterosexism, and other forms of oppression. Not all agree that change is needed in the oftentimes invisible ways that schools and society favor or privilege certain groups or identities and disadvantage or marginalize others (Kumishiro, 2009). There are major efforts to recruit more diverse and qualified people into the teaching workforc e, specifically in Florida with such programs as Florida Fund for Minority Teachers, Jacksonville Teacher Residency Program, the M.I.S.T.E.R (Mentoring Instructing Students Toward Effective Role Models) Program, and the Teacher Incentive Fund (TIF) in Oran ge County Public Schools. However, for people of color, especially African American men, these efforts may b e thwarted partly due to the hiring practices currently shaping who is more likely to be hired for the critical vacant position. In fact, African Am erican men, which are one of the most targeted groups who are sought after to become a larger part of the teaching population in Florida are often less likely to be hired for positions than their white male (and sometimes female) counterparts, and there a re most likely underlying biases that could be 2017).

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198 Ultimately, more research should explore not only who is being recruited into the field, but also what assum ptions are made when correlating which groups are more motivated and hold a greater desire to become a teacher based on current representation in the field, and more focused on who is being hired. There may be a rich pool of diverse, qualified teachers eag er to give back to society, promote social justice, and help the next generation of students reach their highest potential, but they remain excluded from the teaching population because they are not given similar employment opportunities. Implication and D irections for Future Research 4 : Beyond Motivations to Become a Teacher: The Motivations to Improve the Educational System One potential role for motivational theory education researchers is to create spaces where more teachers can voice their opinions, go als, and motivations for their work, as well as assist in connecting and bridging this wealth of information from theory into practice with regard to both teacher preparation programs and teacher professional development and retention programs. Researchers should also be willing to learn with and from these teachers in advancing motivational, educational, and reform frameworks and initiatives, as well as encouraging other stakeholders administrators, community members, school district leaders and policy mak ers survey, these teachers are not only willing, but also actively requesting to participate and be included in educational reform and research. That being said, follow up is essential for efforts for teacher recruitment, prepara tion, and retention (Smith, Watt, & Richardson, 2017). Findings from this study could be complemented with additional research studies that provide a place for teachers to share their voices through interviews, focus groups, and continuous

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199 (longitudinal) d ata collection and analysis. Finally, this study provides a solid foundation on which to build future studies not only on educational reform efforts for current Florida public school K 12 teachers, but also expanded and applied to other Florida teacher pop ulations, such as private, charter, parochial, and virtual school teachers. Additionally, f urther quantitative studies using other methods and analyses, as well as qualitative studies, are needed to expand the breadth and depth of the baseline information I provided in this study. The interconnectedness of all of these elements -the purpose of schools, the promotion of White Anglo Saxon Protestant middle class heterosexual values, the perception of gender and race, the professionalization (or lack thereof) of the field of education, and the state of the national and global economy -have all influenced how prospective teachers were a) permitted and b) prepared to become teachers. All of these factors greatly impact the role, expectations, and perceived capabi lities, and ultimately motivations of who should and should not become a teacher, e specially with regard to potential occupational opportunities. Further research is needed to more deeply examine the psychological, cultural, historical, and sociological fa Implication and Directions for Future Research 5 : The FIT Choice as a Predictor for Satisfaction Based on my sample, one final implication that the FIT Choice scale could be better utilized for measur ing/predicting satisfaction of teaching as opposed to their motivations to teach. I discovered that if all of the dependent variables (DVs) were turned into independent variables (IVs,) the scores in my data set could be used to predict how satisfied teachers were with their choice of choosing teaching as a career. Given that the FIT Choice Scale has not previously been tested for reliability and validity within the context of my population, it is not unlikely that there may be alternative wa ys in which to use it.

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200 Below in Figure 5 1, two example MR outputs are included to provide evidence of how my model and the variables which I analyzed could be used to predict satisfaction in future research. The first regression output has all of the curr ent DVs, except for satisfaction of choice, changed and entered into the regression as IVs with of my current IVs. The second regression output has only the current DVs as predictors of satisfaction. Output 1: DVs and IVs: Results of the first regression a nalysis showed the overall model explains 14.7% of the variance ( R 2 = 14.7, F (25, 3704) = 25.54, p < .001) of satisfaction with choosing a career in teaching. Output 2: DVs only: Results of the second regression analysis showed that the overall model expla ins 16.3% of the variance ( R 2 = 16.3, F (12, 7107) = 115.064, p < .001) of satisfaction with choosing a career in teaching. Finally, it may be beneficial to revert to the original use of the FIT Choice Scale to examine preservice teachers motivations for choosing teaching as a career However, t his in itself creates barriers, especially in Florida, as the state offers 433 avenues to teaching certification and it at all of those settings at the same time Conclusion Despite the negative social stigma, many people are still motivated to become and remain improve social inequities, & Coulthard, 2000; Richardson, Karabenick, & Watt, 2014; Spring, 2016; Yu & Bieger; 2013). Overall, working with children and adolescents is viewed across the education landscape as perhap s the greatest motivational factor for entering the teaching profession (Balyer & zcan,

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201 education affects so many facets of American society, the stakes are incredibly hi gh for the depends on the quality of its education system, which in turn depends directly on how teachers l Research Council, 2010, p. 185 186). Of the 8,420 respondents, over a third of the participants said they were willing to complete follow up studies (~4,500) within the survey. Additionally over 100 participants emailed/personally reached out to me to no t only thank me for the opportunity to participate in by study, and also stated their further willingness to participate in future studies. The commitment that many Florida teachers have for their students is made more profound by the fact that so many par ticipants, whether in the survey or through direct correspondence, also wished me luck and encouraged me in my studies. This further supports the belief that Florida teachers truly do care about their students and their community, and want to give back and impact future generations, even students with whom they have brief encounters. Until the gaps that currently exist between understanding what motivates people to choose teaching as a career, how different factors motivate different people to the field, an d which pathways are preferred by whom, are filled, recruitment efforts will most likely continue to maintain the status quo. narrow slice of graduates, the status of the profession will rem ain what it is today below that of 541). This shortfall is where motivational theory can have a significant impact on guiding educational stakeholders to seek the best candidates for their particular programs and/or if programmatic changes need to be made.

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202 As American public schools continue to face ever growing challenges to improve the quality of K 12 education, in reality these programs and initiatives have operated within the context of a volatile society. While teacher education programs and educational researchers have there are still insurmountable challeng es remaining. One potential weakness in these teacher reform efforts is that the changes may have omitted the consideration of the motivations, aspirations, and goals of teachers themselves. Historically, practicing teachers have not typically had the powe r to make systemic and lasting changes within their own profession. Often, due to their influence and power, external educational stakeholders, whether they are researchers, policy makers, or government agencies have had the luxury of making decisions conc erning a profession that typically does not impact their livelihood on a daily basis. Teachers, however, do not have this indulgence: reformers who try to change them, [teachers] rarely have had the luxury of p icking a side and staying on it (Cohen, 1989, p. 404). More initiatives and research are needed to include the original motivations for choosing such a demanding career that is often held with little esteem provide important insights as to how their professional identities are formed and change over time. This delicate balance had to be maintained not only by practicing teachers, but also by those instructors and institutions that educate them. The FIT Choice Scale and Survey provides the methodologically grounded, vetted framework upon which researchers could build great knowledge that, in turn, could drastically reform the education landscape in and tracking these motivations over time can influence teache r preparation in every aspect

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203 t raditional, alternative, and countless variations leading to great change in the industry. Ultimate ly, with the goal to recruit, prepare, support, and retain more and better teachers in the U.S., the FIT Choice Scale and understanding motivations could be the turning point that is greatly needed in teacher and education reform.

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204 APPENDIX A ADDITIONAL IN FORMATION FOR CHAPTER 3: FACTOR LOADINGS AND CFA MODEL DIAGRAMS Factors Item Factor loading (SD) Factors Item Factor loading(SD) Self perceptions of Teaching Ability Q11 0.815 (0.010) Shape Future of Children/Adolescents Q15 0.804 (0.008) Q25 0.869 (0. 010) Q28 0.851 (0.006) Q43 0.594 (0.013) Q48 0.875 (0.006) Intrinsic Career Value Q6 0.816 (0.011) Enhance Social Equity Q37 0.868 (0.006) Q13 0.572 (0.010) Q47 0.894 (0.005) Q18 0.713 (0.012) Q49 0.828 (0.007) Fallback Career Q17 0.137 (0.015) Make Social Contribution Q12 0.810 (0.008) Q36 0.653 (0.045) Q26 0.830 (0.008) Q46 0.691 (0.048) Q35 0.866 (0.007) Personal Utility Value (Higher order Factor) By Job Sec 0.761 (0.011) Social Utility Value (Higher Order Factor) By Shape 0.982 (0.0 05) By Fam Time 0.755 (0.010) By Enhance 0.798 (0.008) By Job Trans 0.894 (0.011) By Soc Change 0.856 (0.009) By Work w Child 0.698 (0.012) Job Security Q20 0.715 (0.008) Work with Children/Adolescents Q19 0.902 (0.005) Q32 0.767 (0.007) Q31 0.870 (0.005) Q40 0.874 (0.006) Q39 0.850 (0.006) Time for Family Q7 0.539 (0.009) Prior Teaching & Learning Experience Q23 0.893 (0.006) Q21 0.780 (0.006) Q34 0.940 (0.006) Q33 0.891 (0.004) Q41 0.685 (0.010) Q9 0.719 (0.007) Social Influences Q8 0.766 (0.008) Q24 0.576 (0.009) Q29 0.738 (0.009) Job Transferability Q14 0.576 (0.011) Q42 0.826 (0.008) Q27 0.633 (0.010) Q45 0.721 (0.009) Figure A 1 : Scale I Influential Factors About Teaching Models Fit.

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205 Factors Item Factor loadi ng (SD) Task Expertise Q60 0.746 (0.009) Q64 0.747 (0.009) Q65 0.906 (0.007) Task Difficulty Q52 0.760 (0.008) Q56 0.864 (0.008) Q61 0.738 (0.009) Social Status Q54 1.000 (0.000) Q57 0.990 (0.013) Q62 1.062 (0.012) Q55 0.764 (0.013) Q59 1.040 (0.013) Q63 0.968 (0.014) Salary Q51 0.857 (*) Q53 0.899 (*) *No SD as only contains two items Figure A 2: Scale II Beliefs About Teaching Models Fit. Factors Item Factor loading(SD) Social Dissuasion Q68 0.593 (0.011) Q70 0.587 (0.011) Q72 0.940 (0.012) Satisfaction with Choice** Q67 ** 0.227 (0.013) Q69 0.927 (0.012) Q71 0.972 (0.012) ** Omitted Figure A 3. Scale III Decision to Become a Teacher Model Fit

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206 Figure A 4. CFA Model Diagram: Self perception s of Teaching Ability. Fig ure A 5. CFA Model Diagram: Intrinsic Career Value.

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207 Figure A 6. CFA Model Diagram: Personal Utility Value.

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208 Figure A 7. CFA Model Diagram: Social Utility Value.

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209 Figure A 8. CFA Model Diagram: Prior Teaching and Learning Experiences. Figure A 9. CFA Model Diagram: Social Influence.

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210 Figure A 10. CFA M odel Diagram: Task Difficulty. Figure A 11. CFA Model Diagram: Task Expertise.

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211 Figure A 12. CFA Model Diagram: Social Status.

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212 Figure A 13. CFA Model Diagram: Social Dissuasion. Figure A 14. CFA Model Diagram: Satisfaction with Choice.

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213 Figure A 15. CFA Model Diagram: Salary.

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214 APPENDIX B ADDITIONAL INFORMATION FOR CHAPTER 3 CORRELATION MATRICES Ability Q11_1 Q25_1 Q43_1 Q11_1 1.000 .708 .483 Q25_1 .708 1.000 .516 Q43_1 .483 .516 1.000 Figure B 1. Ability Inter Item Correlation Matrix Intrinsic Q6_1 Q13_1 Q18_1 Q6_1 1.000 .465 .579 Q13_1 .465 1.000 .407 Q18_1 .579 .407 1.000 Figure B 2. Intrinsic Inter Item Correlation Matrix Fallback Q17_1 Q36_1 Q46_1 Q17_1 1.000 .280 .380 Q36_1 .280 1.000 .448 Q46_1 .380 .448 1.000 Figure B 3. Fallback Inter Item Correlation Matrix Job Security Q20_1 Q32_1 Q40_1 Q20_1 1.000 .527 .625 Q32_1 .527 1.000 .680 Q40_1 .625 .680 1.000 Figure B 4. Job Security Inter Item Correlation Matrix

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215 Time for Family Q7_1 Q9_1 Q21_1 Q24_1 Q33_1 Q7_1 1.000 .414 .493 .320 .456 Q9_1 .414 1.000 .492 .535 .642 Q21_1 .493 .492 1.000 .400 .721 Q24_1 .320 .535 .400 1.000 .475 Q33_1 .456 .642 .721 .475 1.000 Figure B 5 Time for Fa mily Inter Item Correlation Matrix Job Transferability Q14_1 Q27_1 Q45_1 Q14_1 1.000 .355 .431 Q27_1 .355 1.000 .454 Q45_1 .431 .454 1.000 Figure B 6. Job Transferability Inter Item Correlation Matrix Personal Utility Value job family jtrans job 1.000 .472 .523 family .472 1.000 .527 jtrans .523 .527 1.000 Figure B 7 Personal Utility Value Inter Item Correlation Matrix Shape future of Children/Adolescents Q15_1 Q28_1 Q48_1 Q15_1 1.000 .723 .696 Q28_1 .723 1.000 .726 Q48_1 .696 .726 1.000 Figure B 8 Shape future of Children/Adolescents Inter Item Correlation Matrix Enhance Social Equity Q37_1 Q47_1 Q49_1 Q37_1 1.000 .768 .695 Q47_1 .768 1.000 .770 Q49_1 .695 .770 1.000 Figure B 9 Enhance Social Equity Inter Item Correlation Mat rix

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216 Make Social Contribution Q12_1 Q26_1 Q35_1 Q12_1 1.000 .683 .704 Q26_1 .683 1.000 .712 Q35_1 .704 .712 1.000 Figure B 10 Make Social Contribution Inter Item Correlation Matrix Work with Children/Adolescents Q19_1 Q31_1 Q39_1 Q19_1 1.000 .799 .764 Q31_1 .799 1.000 .723 Q39_1 .764 .723 1.000 Figure B 1 1 Work with Children/Adolescents Inter Item Correlation Matrix Social Utility Value shape equity cont work shape 1.000 .675 .735 .735 equity .675 1.000 .661 .661 cont .735 .661 1.000 1.0 00 work .735 .661 1.000 1.000 Figure B 1 2 Social Utility Value Inter Item Correlation Matrix Prior Teaching & Learning Experiences Q23_1 Q34_1 Q41_1 Q23_1 1.000 .840 .612 Q34_1 .840 1.000 .644 Q41_1 .612 .644 1.000 Figure B 1 3 Prior Teaching & Learning Experiences Inter Item Correlation Matrix Social Influences Q8_1 Q29_1 Q42_1 Q8_1 1.000 .568 .634 Q29_1 .568 1.000 .610 Q42_1 .634 .610 1.000 Figure B 1 4 Social Influences Inter Item Correlation Matrix

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217 Expertise Q60_1 Q64_1 Q65_1 Q60_1 1.000 .558 .676 Q64_1 .558 1.000 .677 Q65_1 .676 .677 1.000 Figure B 1 5 Expertise Inter Item Correlation Matrix Difficulty Q52_1 Q56_1 Q61_1 Q52_1 1.000 .657 .562 Q56_1 .657 1.000 .639 Q61_1 .562 .639 1.000 Figure B 1 6 Difficulty Inter Item Co rrelation Matrix Social Status Q54_1 Q55_1 Q57_1 Q59_1 Q62_1 Q63_1 Q54_1 1.000 .548 .626 .621 .642 .541 Q55_1 .548 1.000 .479 .464 .448 .440 Q57_1 .626 .479 1.000 .662 .634 .690 Q59_1 .621 .464 .662 1.000 .729 .639 Q62_1 .642 .448 .634 .729 1.000 .6 43 Q63_1 .541 .440 .690 .639 .643 1.000 Figure B 1 7 Social Status Inter Item Correlation Matrix Social Dissuasion Q68_1 Q70_1 Q72_1 Q68_1 1.000 .348 .557 Q70_1 .348 1.000 .552 Q72_1 .557 .552 1.000 Figure B 1 8 Social Dissuasion Inter Item Corre lation Matrix Satisfaction with Choice Q67_1 Q69_1 Q71_1 Q67_1 1.000 .211 .221 Q69_1 .211 1.000 .901 Q71_1 .221 .901 1.000 Figure B 1 9 Satisfaction with Choice Inter Item Correlation Matrix

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218 APPENDIX C MULTICOLLINEARITY TESTS, HISTOGRAM, P PLOT, AN D SCATTERPLOT DIAGRAMS FOR 13 DEPENDENT VARIABLES Ability Coefficients a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Tolerance VIF (Constant) 5.978 _Age .005 .022 .029 .0 29 .922 1.084 male_female .087 .061 .061 .061 .969 1.032 others_female .050 .033 .035 .035 .983 1.017 Spa_Eng .174 .014 .005 .005 .788 1.270 Others_Eng .268 .008 .007 .007 .964 1.037 Black_white 1.141 .012 .011 .011 .9 75 1.026 others_white .110 .010 .010 .010 .769 1.300 Work Experience Non Teach Y/N Q93_code .089 .014 .007 .007 .938 1.067 Alternative Y/N Q125_code .188 .037 .027 .027 .689 1.452 Prior Edu Coursework Y/N Q128_code .038 .012 .014 .014 .953 1.049 Prior Teaching Experience Y/N Q137_code .163 .009 .016 .015 .693 1.442 Master and Graduate Course .072 .014 .003 .003 .936 1.068 Length of Program Prior to Teaching _Q131_weeks .001 .035 .027 .027 .948 1.054 Figure C 1 Tests for Multicollinearit y, Ability.

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219 Figure C 2. Histogram, P Plot, and Scatterplot for Ability

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220 Intrinsic Career Value Coefficients a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero orde r Partial Part Tolerance VIF (Co nstant) 5.473 _Age .006 .012 .024 .023 .922 1.084 male_female .218 .113 .094 .093 .969 1.032 others_female .026 .030 .033 .032 .983 1.017 Spa_Eng .342 .043 .030 .029 .788 1.269 Others_Eng .403 .018 .018 .017 .965 1.036 Black_white 1.328 .016 .011 .010 .975 1.026 others_white .157 .024 .019 .019 .771 1.296 Work Experience Non Teach Y/N Q93_code .274 .095 .068 .066 .937 1.067 Alternative Y/N Q125_code .394 .138 .073 .071 .689 1.452 Prior Edu Coursework Y/N Q128_code .074 .011 .004 004 .953 1.049 Prior Teaching Experience Y/N Q137_code .005 .109 .032 .032 .693 1.442 Master and Graduate Course .042 .027 .047 .046 .937 1.067 Length of Program Prior to Teaching _Q131_weeks .001 .099 .066 .064 .948 1.055 Figure C 3. Tests fo r Multicollinearity, Intrinsic Career Value

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221 Figure C 4. Histogram, P Plot, and Scatterplot for Intrinsic Career Value

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222 Fallback Career Figure C 5. Tests for Multicollinearity, Fallback Career Coefficients a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Tolerance VIF (Constant) 2.292 _Age .001 .018 .043 .042 .923 1.084 male_female .418 .119 .106 .104 .970 1.031 others_female .531 .015 .014 .014 .983 1.017 Spa_Eng .250 .040 .019 .019 .787 1.271 Others_Eng .212 .005 .002 .002 .964 1.038 Black_white 1.452 .022 .020 .020 .975 1.026 others_white .168 .055 .029 .029 .769 1.301 Work Experience Non Teach Y/N Q93_code .022 .047 .022 .022 .937 1.067 Alternative Y/N Q125_code .118 .133 .066 .065 .689 1.452 Pr ior Edu Coursework Y/N Q128_code .149 .044 .031 .030 .953 1.049 Prior Teaching Experience Y/N Q137_code .251 .115 .038 .037 .695 1.439 Master and Graduate Course .150 .018 .036 .035 .936 1.069 Length of Program Prior to Teaching _Q131_weeks .000 .08 4 .059 .058 .948 1.055

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223 Figure C 6. Histogram, P Plot, and Scatterplot for Fallback Career

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224 Personal Utility Value Figure C 7. Tests for Multicollinearity, Personal Utility Value Coefficients a Model 95.0% Confidence Interval for B Correlations Co llinearity Statistics Upper Bound Zero order Partial Part Toleranc e VIF 1 (Constant) 4.030 _Age .003 .051 .056 .056 .922 1.085 male_female .019 .020 .026 .026 .971 1.030 others_female .193 .017 .018 .018 .985 1.015 Spa_Eng .244 .0 20 .009 .009 .785 1.273 Others_Eng .289 .002 .001 .001 .965 1.036 Black_white 1.199 .004 .003 .003 .975 1.026 others_white .143 .027 .010 .010 .769 1.300 Work Experience Non Teach Y/N Q93_code .014 .030 .026 .026 .937 1.067 Alternative Y/N Q12 5_code .116 .049 .003 .003 .684 1.462 Prior Edu Coursework Y/N Q128_code .163 .036 .024 .023 .953 1.050 Prior Teaching Experience Y/N Q137_code .420 .080 .062 .062 .689 1.450 Master and Graduate Course .072 .021 .005 .005 .936 1.069 Length of Program Prior to Teaching _Q131_weeks .000 .025 .012 .012 .947 1.056

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225 Figure C 8. Histogram, P Plot, and Scatterplot for Personal Utility Value

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226 Social Utility Value Coefficien ts a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Toleranc e VIF 1 (Constant) 6.268 _Age .003 .059 .056 .055 .923 1.083 male_female .031 .040 .040 .040 .969 1.032 others _female .190 .035 .046 .045 .982 1.018 Spa_Eng .368 .075 .035 .035 .787 1.271 Others_Eng .373 .026 .015 .015 .964 1.037 Black_white 1.382 .016 .013 .013 .975 1.026 others_white .319 .101 .072 .071 .769 1.300 Work Experience Non Teach Y/N Q93_ code .021 .012 .023 .023 .936 1.068 Alternative Y/N Q125_code .067 .016 .013 .013 .686 1.458 Prior Edu Coursework Y/N Q128_code .051 .005 .012 .012 .953 1.049 Prior Teaching Experience Y/N Q137_code .150 .016 .006 .006 .691 1.447 Master an d Graduate Course .130 .017 .021 .021 .935 1.069 Length of Program Prior to Teaching _Q131_weeks .001 .021 .017 .016 .948 1.055 Figure C 9. Tests for Multicollinearity, Social Utility Value

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227 Figure C 10. Histogram, P Plot, and Scatterplot for S ocial Utility Value

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228 Prior Teaching a nd Learning Experiences Coefficients a Model 95.0% Confiden ce Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Toleranc e VIF 1 (Constant) 6.122 _Age .002 .057 .046 .046 .922 1.085 male_female .166 .003 .011 .010 .970 1.031 others_female .198 .042 .044 .044 .983 1.017 Spa_Eng .228 .012 .004 .004 .788 1.269 Others_Eng .237 .002 .006 .006 .964 1.038 Black_white 1.790 .016 .017 .017 .975 1.026 others_w hite .189 .019 .020 .020 .769 1.300 Work Experience Non Teach Y/N Q93_code .223 .051 .038 .038 .938 1.066 Alternative Y/N Q125_code .257 .038 .027 .026 .685 1.460 Prior Edu Coursework Y/N Q128_code .021 .043 .038 .038 .953 1.050 Prior Teaching Experience Y/N Q137_code .172 .019 .005 .005 .689 1.450 Master and Graduate Course .086 .002 .002 .002 .935 1.069 Length of Program Prior to Teaching _Q131_weeks .000 .000 .013 .012 .948 1.055 Figure C 1 1. Tests for Multicollinearity, Prior Tea ching a nd Learning Experiences

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229 Figure C 12. Histogram, P Plot, and Scatterplot for Prior Teaching a nd Learning Experiences

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230 Social Influences Coefficients a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Z ero order Partial Part Toleran ce VIF 1 (Constant) 3.780 _Age .002 .047 .043 .043 .923 1.083 male_female .317 .041 .032 .032 .970 1.031 others_female .191 .021 .021 .021 .983 1.017 Spa_Eng .095 .017 .019 .019 .786 1.272 Others_Eng .467 .011 .008 .008 .964 1.038 Black_white .915 .017 .011 .011 .975 1.026 others_white .191 .010 .011 .010 .768 1.301 Work Experience Non Teach Y/N Q93_code .126 .010 .000 .000 .938 1.067 Alternative Y/N Q125_code .043 .059 .023 .023 .687 1. 455 Prior Edu Coursework Y/N Q128_code .087 .002 .009 .009 .953 1.049 Prior Teaching Experience Y/N Q137_code .457 .068 .045 .045 .691 1.447 Master and Graduate Course .049 .055 .044 .044 .936 1.068 Length of Program Prior to Teaching _Q131_w eeks .001 .009 .008 .008 .947 1.056 Figure C 1 3. Tests for Multicollinearity, Social Influences

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231 Figure C 14. Histogram, P Plot, and Scatterplot for Social Influences

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232 Expertise Coefficients a Model 95.0% Confidenc e Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Toleranc e VIF 1 (Constant) 5.252 _Age .004 .013 .004 .004 .922 1.084 male_female .276 .039 .037 .037 .969 1.032 others_female .500 .002 .001 .001 .983 1.017 Spa_Eng .468 .054 .039 .039 .790 1.266 Others_Eng .660 .042 .037 .037 .964 1.038 Black_white 1.276 .007 .003 .003 .975 1.026 others_white .192 .050 .021 .021 .772 1.295 Work Experience Non Teach Y/N Q93_code .114 .005 .004 .004 .937 1.067 Alternative Y/N Q125_code .127 .010 .003 .003 .687 1.456 Prior Edu Coursework Y/N Q128_code .039 .019 .019 .019 .953 1.050 Prior Teaching Experience Y/N Q137_code .213 .021 .013 .013 .691 1.447 Master and Graduate Course .216 .049 .041 .041 .937 1.068 Length of Program Pr ior to Teaching _Q131_weeks .001 .019 .017 .017 .947 1.056 Figure C 1 5. Tests for Multicollinearity, Expertise

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233 Figure C 16. Histogram, P Plot, and Scatterplot for Expertise

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234 Difficulty Coefficients a Model 95.0% Confidence Interval for B Correl ations Collinearity Statistics Upper Bound Zero order Partial Part Tolera nce VIF 1 (Constant) 5.928 _Age .011 .118 .110 .109 .923 1.084 male_female .209 .007 .013 .013 .970 1.031 others_female .276 .012 .016 .016 .983 1.017 Spa_Eng 384 .047 .019 .019 .787 1.270 Others_Eng .577 .028 .020 .020 .964 1.037 Black_white 2.115 .019 .017 .017 .975 1.026 others_white .335 .074 .047 .046 .770 1.298 Work Experience Non Teach Y/N Q93_code .172 .026 .014 .014 .938 1.066 Alternative Y/N Q125_code .075 .026 .017 .016 .691 1.447 Prior Edu Coursework Y/N Q128_code .177 .020 .017 .017 .954 1.048 Prior Teaching Experience Y/N Q137_code .255 .024 .014 .014 .696 1.436 Master and Graduate Course .065 .030 .012 .012 .936 1.068 Length of Program Prior to Teaching _Q131_weeks .001 .021 .020 .020 .948 1.054 Figure C 1 7. Tests for Multicollinearity, Difficulty

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235 Figure C 18. Histogram, P Plot, and Scatterplot for Difficulty

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236 Social Status Coefficients a Model 95.0% Confidence Int erval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Toleranc e VIF 1 (Constant) 3.683 _Age .006 .016 .017 .017 .923 1.083 male_female .126 .001 .001 .001 .969 1.032 others_female .416 .008 .005 .005 .983 1 .017 Spa_Eng .260 .012 .007 .007 .789 1.268 Others_Eng .545 .022 .023 .023 .965 1.036 Black_white 1.027 .003 .005 .005 .975 1.026 others_white .123 .009 .001 .001 .772 1.296 Work Experience Non Teach Y/N Q93_code .089 .010 .005 .005 .938 1. 067 Alternative Y/N Q125_code .269 .005 .027 .027 .687 1.455 Prior Edu Coursework Y/N Q128_code .271 .059 .051 .051 .954 1.049 Prior Teaching Experience Y/N Q137_code .323 .030 .034 .033 .693 1.444 Master and Graduate Course .007 .035 .033 .033 .937 1.067 Length of Program Prior to Teaching _Q131_weeks .001 .013 .016 .016 .948 1.055 Figure C 1 9. Tests for Multicollinearity, Social Status

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237 Figure C 20. Histogram, P Plot, and Scatterplot for Social Status

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238 Salary Coefficients a Model 95. 0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Toleranc e VIF 1 (Constant) 2.073 _Age .013 .083 .074 .073 .923 1.084 male_female .164 .020 .010 .010 .970 1.03 1 others_female .624 .009 .009 .009 .983 1.017 Spa_Eng .115 .012 .013 .013 .789 1.268 Others_Eng .055 .027 .025 .025 .964 1.037 Black_white 1.489 .008 .009 .009 .975 1.026 others_white .096 .017 .005 .005 .771 1.297 Work Experience Non Teach Y/N Q93_code .047 .036 .017 .016 .938 1.067 Alternative Y/N Q125_code .234 .014 .022 .022 .689 1.451 Prior Edu Coursework Y/N Q128_code .195 .040 .031 .031 .954 1.049 Prior Teaching Experience Y/N Q137_code .328 .047 .038 .037 .694 1.441 Master and Graduate Course .056 .006 .012 .012 .936 1.068 Length of Program Prior to Teaching _Q131_weeks .000 .042 .031 .031 .948 1.055 Figure C 2 1 Tests for Multicollinearity, Salary

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239 Figure C 22. Histogram, P Plot, and Scatterplot for Salary

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240 Social Dissuasion Coef ficients a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partia l Part Toleranc e VIF 1 (Constant) 5.789 _Age .021 .156 .174 .171 .923 1.084 male_female .434 .058 .059 .057 .970 1.031 othe rs_female .497 .003 .004 .004 .982 1.018 Spa_Eng .592 .074 .043 .042 .789 1.268 Others_Eng .567 .029 .018 .017 .964 1.037 Black_white 1.494 .002 .002 .002 .975 1.026 others_white .447 .114 .070 .068 .770 1.298 Work Experience Non Teach Y/N Q93_ code .190 .064 .079 .077 .937 1.068 Alternative Y/N Q125_code .087 .078 .047 .046 .688 1.453 Prior Edu Coursework Y/N Q128_code .082 .048 .052 .051 .953 1.050 Prior Teaching Experience Y/N Q137_code .231 .054 .009 .008 .692 1.445 Master and Graduate Course .287 .019 .049 .048 .936 1.069 Length of Program Prior to Teaching _Q131_weeks .000 .041 .034 .033 .948 1.055 Figure C 23. Tests for Multicollinearity, Social Dissuasion

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241 Figure C 24. Histogram, P Plot, and Scatterplot fo r Social Dissuasion

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242 Satisfaction with Choice Coefficients a Model 95.0% Confidence Interval for B Correlations Collinearity Statistics Upper Bound Zero order Partial Part Tolerance VIF 1 (Constant) 5.236 _Age .019 .127 .130 .129 .924 1.083 ma le_female .029 .015 .024 .023 .969 1.032 others_female .009 .031 .032 .031 .982 1.018 Spa_Eng .323 .018 .019 .018 .787 1.271 Others_Eng .347 .002 .005 .005 .964 1.038 Black_white 1.915 .024 .021 .020 .975 1.026 others_white .057 .020 .01 5 .015 .769 1.300 Work Experience Non Teach Y/N Q93_code .209 .018 .034 .033 .938 1.067 Alternative Y/N Q125_code .139 .008 .000 .000 .688 1.454 Prior Edu Coursework Y/N Q128_code .107 .012 .003 .003 .953 1.050 Prior Teaching Experience Y/N Q137_c ode .156 .001 .002 .002 .693 1.443 Master and Graduate Course .062 .018 .010 .010 .937 1.067 Length of Program Prior to Teaching _Q131_weeks .001 .020 .019 .019 .948 1.055 Figure C 25. Tests for Multicollinearity, Satisfaction w ith Choice

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243 F igure C 26. Histogram, P Plot, and Scatterplot for Satisfaction w ith Choice

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244 APPENDIX D TEACHER CHARACTERISTICS AND DEMOGRAPHICS Figure D 1. District Name respondents (Alachua Lee)

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245 Figure D 2 District Name respondents ( Leon Walton )

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246 Figure D 3 D istrict Name respondents bar chart MilitaryYes_No Frequency Percent Valid Percent Cumulative Percent Valid 17 .2 .2 .2 No 7385 94.3 94.3 94.5 Yes 432 5.5 5.5 100.0 Total 7834 100.0 100.0 Figure D 4 Military respondents Figure D 5 Milita ry respondents bar chart

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247 Base Salary Frequency Percent Valid Percent Cumulative Percent Valid 110 1.4 1.4 1.4 $10,000 $24,999 110 1.4 1.4 2.8 $25,000 $49,999 5105 65.2 65.2 68.0 $50,000 $74,999 2287 29.2 29.2 97.2 $75,000 and over 186 2.4 2.4 9 9.5 Under $10,000 36 .5 .5 100.0 Total 7834 100.0 100.0 Figure D 6 Base salary Figure D 7 Base salary bar chart

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248 Rural Suburban Frequency Percent Valid Percent Cumulative Percent Valid 120 1.5 1.5 1.5 Rural 1241 15.8 15.8 17.4 Suburban 3982 50.8 50.8 68.2 Urban 2491 31.8 31.8 100.0 Total 7834 100.0 100.0 Figure D 8 Geographical Breakdown Figure D 9 Geographical Breakdown bar chart

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249 Title1 Yes_No Frequency Percent Valid Percent Cumulative Percent Valid 117 1.5 1.5 1.5 No 3138 40.1 40.1 41.5 Yes 4579 58.5 58.5 100.0 Total 7834 100.0 100.0 Figure D 10 Title 1 school respondents Figure D 11 Title 1 school respondents bar chart

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250 Bachelor Yes_No Frequency Percent Valid Percent Cumulative Percent Valid 123 1 .6 1.6 1.6 No 456 5.8 5.8 7.4 Yes 7255 92.6 92.6 100.0 Total 7834 100.0 100.0 Figure D 12 Degree level Figure D 13 Degree level bar chart

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251 Alternative Route Frequency Percent Valid Percent Cumulative Percent Valid 5826 74.4 74.4 74.4 Ot her 1952 24.9 24.9 99.3 Teach For America 56 .7 .7 100.0 Total 7834 100.0 100.0 Figure D 14 Route to Certification Figure D 15 Route to certification bar chart Figure D 16 Teacher preparation program recruitment bar chart

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252 APPENDIX E ADDIT IONAL INFORMATION FOR CHAPTER 4 : FULL REGRESSION OUTPUTS FOR ALL 13 VARIABLES Figure E 1 Regression Output for Self Perceptions of Teaching Ability.

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253 Figure E 2. Regression Output for Intrinsic Career Value.

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254 Figure E 3. Regression Output for Fal lback Career.

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255 Figure E 4. Regression Output for Personal Utility Value

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256 Figure E 5 Regression Output for Social Utility Value

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257 Figure E 6. Regression Output for Prior Teaching & Learning Experiences

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258 Figure E 7. Regression Output for Socia l Influences

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259 Figure E 8. Regression Output for Expertise

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260 Figure E 9. Regression Output for Difficulty

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261 Figure E 10. Regression Output for Social Status

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262 Figure E 11. Regression Output for Salary

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263 Figure E 12. Regression Output for So cial Dissuasion

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264 Figure E 13. Regression Output for Satisfaction with Choice

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265 APPENDIX F FINAL FIT CHOICE SURVEY Start of Block: IRB informed consent Q1 Is it the Right "Fit?": Determining Florida Teachers' Motivations for Choosing Teaching as a C areer Using the FIT Choice Scale. My name is Natalie Ridgewell, and I am a Doctoral Candidate in the College of Education School of Teaching and Learning at the University of Florida. I thank you for taking the time to participate in this survey. I have be en a teacher and educator for 12 years, and I understand the daily challenges to find time in your day to do anything extra. Your efforts are appreciated and will make a difference to help future teachers, administrators, and stakeholders understand what h as, and continues to motivate you every day to do the amazing things you do to meet the needs of our students and support them in reaching their highest p otential. Your participation is completely voluntary. The purpose of this survey is to determine the motivations you had to choose teaching as a career. You do not have to answer any question you do not wish to answer, and there is no penalty not to do so. The estimated time to complete the survey is 15 20 minutes. There are no known risks associated wit h this study. This study and researcher have no associations with any social media platforms, and the information will only be used for research purposes. The online host (Qualtrics) uses several forms of encryption and other protections. All answers are c onfidential to the extent provided by law, and your name will not be used in any report. If you would like to learn more about this survey, please contact me, Natalie Ridgewell, at nkr@ufl.edu. If you have questions about your rights as a research pa rticipant, please contact the UFIRB office, P.O. Box 112250, University of Florida, Gainesville, FL, 32611 2250, (352) 392 0433; Reference UFIRB# IRB201701101. By clicking on agree to participate below, you are indicating that you have read the procedure d escribed above and voluntarily agree to participate in the survey. You may print a copy of this question for your record. Q2 By checking "YES" below, I give my informed consent to participate in this study. o Yes (5) o No (6) End of Block: IRB infor med consent Start of Block: Participant Email and District Name

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266 Q189 What is your school email address? ________________________________________________________________ Q190 What is your school district name? _________________________________________ _______________________ End of Block: Participant Email and District Name Start of Block: Why Teach? Q3 Most of these questions will ask you to think back to when you made the choice to become a teacher, before you received any formal preparation. Q4 The main reason why you chose to become a teacher was. . ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ End of Block: Why Teach? Start of Block: Influential Factors Q5 Please remember to think back to your initial motivations w hen you first chose teaching as a career: "I chose to become a teacher because. . Q6 I am interested in teaching. 1 2 3 4 5 6 7

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267 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in you r decision Q7 Part time teaching could allow more family time. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q8 My friends thought I should become a teacher. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q9 As a teacher I would have lengthy holidays. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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268 Page Break

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269 Q10 Please remember to think back to your initial motivations when you first chose teaching as a career: "I chose to become a teacher beca use. . Q11 I have the qualities of a good teacher. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q12 Teaching allows me to provide a service to s ociety. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q13 I've always wanted to be a teacher. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 ( 7) not at all important in your decision o o o o o o o extremely important in your decision

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270 Q14 Teaching is a useful job for me to have when travelling. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) no t at all important in your decision o o o o o o o extremely important in your decision Q15 Teaching allows me to shape child/adolescent values. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all im portant in your decision o o o o o o o extremely important in your decision Page Break

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271 Q16 Please remember to think back to your initial motivations when you first chose teaching as a career: "I chose to become a teacher because. . Q17 I was unsure of what career I wanted. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q18 I like teaching. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q19 I wanted a job that involves working with children/adolescents. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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272 Q20 Teaching offers a steady career path. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q21 Teaching hours fit with the responsibilities of having a family. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Page Break

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273 Q22 Please remember to think back to your initial motivations when you first chose teaching as a career: "I chose to become a teache r because. . Q23 I have had inspirational teachers. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q24 As a teacher I have a short working day. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q25 I have good teaching skills. 1 2 3 4 5 6 7

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274 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q26 Teachers make a worthwhile social contribution. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q27 A teaching qualification is recognised everywhere. 1 2 3 4 5 6 7 1 (1) 2 ( 2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q28 Teaching allows me to influence the next generation. 1 2 3 4 5 6 7

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275 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q29 My family thought I should become a teacher. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 ( 7) not at all important in your decision o o o o o o o extremely important in your decision Page Break

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276 Q30 Please remember to think back to your initial motivations when you first chose teaching as a career: "I chose to become a teacher because. . Q31 I wanted to work in a child/adolescent centered environment. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q32 Teaching provides a reliable income. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q33 School holidays fit i n with family commitments. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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277 Q34 I have had good teachers as role models. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 ( 3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q35 Teaching enables me to 'give back' to society. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q36 I was not accepted into my first choice career. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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278 Q37 Teaching allows me to raise the ambitions of underprivileged youth 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) n ot at all important in your decision o o o o o o o extremely important in your decision Page Break

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279 Q38 Please remember to think back to your initial motivations when you first chose teaching as a career: "I chose to become a teacher because. . Q 39 I like working with children/adolescents. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q40 Teaching is a secure job. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q41 I have had positive learning experiences. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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280 Q42 People I've worked with thought I should become a teacher. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in you r decision Q43 Teaching is a career suited to my abilities. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Page Break

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281 Q44 Please remember to thi nk back to your initial motivations when you first chose teaching as a career: "I chose to become a teacher because. . Q45 A teaching job allows me to choose where I wish to live. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q46 I chose teaching as a last resort career. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q47 Teaching allows me to benefit the socially disadvantaged. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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282 Q48 Teaching allows m e to have an impact on children/adolescents. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q49 Teaching allows me to work against social disadvantage. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision End of Block: Influential Factors Start of Block: Beliefs About Teaching Q50 Now, please remember to think back to your initial beliefs about teaching when you first chose teaching as a career: "My beliefs about teaching were. . Q51 I think teaching is well paid. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in yo ur decision o o o o o o o extremely important in your decision

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283 Q52 I think teachers have a heavy workload. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q 53 I think teachers earn a good salary. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q54 I believe teachers are perceived as professionals. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q55 I think teachers have high morale. 1 2 3 4 5 6 7

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284 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all impo rtant in your decision o o o o o o o extremely important in your decision Q56 I think teaching is emotionally demanding. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your d ecision Q57 I believe teaching is perceived as a high status occupation. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Page Break

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285 Q58 Now, plea se remember to think back to your initial beliefs about teaching when you first chose teaching as a career: "My beliefs about teaching were. . Q59 I think teachers feel valued by society. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 ( 7) not at all important in your decision o o o o o o o extremely important in your decision Q60 I think teaching requires high levels of expert knowledge. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q61 I think teaching is hard work. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision

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286 Q62 I believe teaching is a well respected career. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q63 I think teachers feel their occupation has high social status. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q64 I think teachers need high levels of technical knowledge. 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision Q65 I think teachers need highly specialized knowledge. 1 2 3 4 5 6 7

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287 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all important in your decision o o o o o o o extremely important in your decision End of Block: Beliefs About Teaching Start of Block: Your Decision to Become a Teacher Q66 Now, please remember to think back to your initial decision to become a teacher : Q67 How carefully did you think ab out becoming a teacher? 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all o o o o o o o extremely Q68 Were you encouraged to pursue careers other than teaching? 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all o o o o o o o extremely Q69 How satisfied are you with your choice of becoming a teacher? 1 2 3 4 5 6 7

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2 88 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all o o o o o o o extremely Q70 Did others tell you teaching was not a good career choice? 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all o o o o o o o extremely Q71 How happy are you with your decision to become a teacher? 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all o o o o o o o extremely Q72 Did ot hers influence you to consider careers other than teaching? 1 2 3 4 5 6 7 1 (1) 2 (2) 3 (3) 4 (4) 5 (5) 6 (6) 7 (7) not at all o o o o o o o extremely End of Block: Your Decision to Become a Teacher Start of Block: Demographics Q73 These questions hel p us understand more about you.

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289 Q74 Date of Birth Please enter as mm/dd/yyyy ________________________________________________________________ Q75 Are you of Hispanic or Latino origin? o Yes (23) o No (24) Q76 What is your race or ethnicity? White (1) Black or African American (2) Asian (3) Native Hawaiian or Other Pacific Islander (4) American Indian or Alaska Native (5) Other (6) ________________________________________________ Prefer not to answer (7) Q77 What is your Native Lang uage? ________________________________________________________________

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290 Q78 What is your Gender? o Male (1) o Female (2) o Other (3) ________________________________________________ o Prefer not to answer (4) Page Break

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291 Q79 Have you ever served on active duty in the U.S. Armed Forces, military Reserves, or National Guard? Active duty does not include training for the Reserves or National Guard, but DOES include activation, for example, for the Persian Gulf War. o Yes (39) o No (40) Skip To: Q82 If Have you ever served on active duty in the U.S. Armed Forces, military Reserves, or National Guar... = No Q80 Which best describes your experience in the U.S. Armed Forces, military Reserves, or National Guard? Active duty does not include training for the Reserves or National Guard, but DOES include activation, for example, for the Persian Gulf War. o Yes, now on active duty (1) o Yes, on active duty during the last 12 months, but not now (2) o Yes, on active duty in the past, but not during the last 12 months (3) o No, training for Reserves or National Guard only (4) Q81 When did you serve on active duty in the U.S. Armed Forces? You may choose one or both choices. September 2001 or later (1) September 2000 or earlier (2) Page Break

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292 Q82 DURING THE CURRENT SCHOOL YEAR, what is your base teaching salary for the entire school year? o Under $10,000 (1) o $10,000 $24,999 (2) o $25,000 $49,999 (3) o $50,000 $74,999 (4) o $75,000 and over (5) Q83 DURING THE CURRENT SCHOOL YEAR, do you, or will you, earn additional compensation from working in any job OUTSIDE this school system? Please report amounts in whole dollars. o Yes (5) ________________________________________________ o No (6) Q84 What is your annual HOUSEHOLD income? o Under $10,000 (1) o $10,000 $24,999 (2) o $25,000 $49,999 (3) o $50,000 $74,999 (4) o $75,000 $99,999 (5) o $100,000 and over (6)

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293 Q85 What is your current marital status? o Married (13) o Widowed (14) o Separated (16) o Di vorced (15) o Never married (17) Q86 Are you currently living with a boyfriend/girlfriend or partner? o Yes (1) o No (2) Q87 Are you currently living in a registered domestic partnership or civil union? o Yes (23) o No (24) Q88 What is the numbe r of children in your household? ________________________________________________________________ Page Break

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294 Q89 What is the geographic location of your school? Urban (1) Suburban (2) Rural (3) Q90 Is your current school a Title I school? Y es (23) No (24) Q91 What is the current grade level you are teaching now? Early childhood, preschool, or at least one of grades K 5 (1) At least one of grades 6 8 (2) At least one of grades 9 12 (3) Q92 What was the grade level you taught d uring your first year of full time teaching? Early childhood, preschool, or at least one of grades K 5 (1) At least one of grades 6 8 (2) At least one of grades 9 12 (3) Q93 Do you have prior non teaching work experience? If yes, report amounts in whole years in the box provided. Yes (1) ________________________________________________ No (2) Skip To: Q95 If Do you have prior non teaching work experience? If yes, report amounts in whole years in the box... = No Skip To: Q94 If Do you have pr ior non teaching work experience? If yes, report amounts in whole years in the box... = Yes Q94 Please select your previous work experience/occupation Occupation Field (1) Role (2) (1008)

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295 Page Break

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296 If you have ter Yes (23) No (24) Q96 Was at least a portion of the cost of your bachelor's degree paid for by a STATE, SCHOOL, or SCHOOL DISTRICT in which you taught? Yes (25) If yes, what was the type of support? (26) ______________________________________ __________ No (27) Q97 What is the name of the college or university where you earned this degree? ________________________________________________________________ Q98 In which city was your university? __________________________________ ______________________________ Q99 In which state was your university? ________________________________________________________________ Q185 In which country was your university? ________________________________________________________________ Q1 00 ________________________________________________________________

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297 Please mark only one option. Education (1) of Education (2) Q102 Plea se select your major field of study from the options below Department (1) Specific Major (2) Q103 Did you have a second major field of study? Please do NOT report academic minors or concentrations. Yes (23) No (24) Skip To: Q105 If Did you have a second major field of study? Pleas e do NOT report academic minors or concentration... = No Display This Question: If Did you have a second major field of study? Please do NOT report academic minors or concentration... = Yes Q104 What was your second major field of study? Department (1) Major Field of Study (2) Q105 Did you have a minor field of study? Yes (23) No (24) Display This Question: If Did you have a minor field of study? = Yes Q106 What was your minor field of study? Department (1)

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298 Minor Fiel d of Study (2) Page Break

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299 level degree? If you have more than one, information about additional degrees will be asked la ter. o Yes (23) o No (24) level degree? If you have more than one, information ab... = Yes level degree? If you have more than on e, information ab... = No level degree paid for by a STATE, SCHOOL, or SCHOOL DISTRICT in which you taught? Yes (25) If yes, what was the type of support? (26) _______________ _________________________________ No (27) Q186 What was the name of your university? ________________________________________________________________ Q118 In which city was your university? _________________________________________________________ _______ Q109 In which city was your university? ________________________________________________________________ Q110 In which state was your university?

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300 ________________________________________________________________ Q111 In which country was yo ur University? ________________________________________________________________ level degree? Department (1) Major Field of Study (2) ther (97) level degree? Please mark only one option. Education (1) It was awarded by another college, school, or department NOT in education (2) level degree? ________________________________________________________________ Page Break

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301 Q115 Do you have level degree? Yes (23) No (24) level degree? = Yes Skip To: End of Block If Do you have an additional ma level degree? = No level degree paid for by a STATE, SCHOOL, or SCHOOL DISTRICT in which you taught? Yes (25) If yes, what was the type of support? ( 26) ________________________________________________ No (27) Q117 What is the name of the college or university where you earned this degree? ________________________________________________________________ Q119 In which state was your university ? ________________________________________________________________ Q120 In what country was your university? ________________________________________________________________ e level degree? Department (1) Major Field of Study (2)

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302 level degree? Please mark only one option. It was awarded b Education (1) It was awarded by another college, school, or department NOT in education (2) level degree? ________________________________________________________________ Q124 These questions will help me understand more about your teacher preparation. Do the best you can to recall how your program was designed or structured. End of Block: Demographics St art of Block: Teacher Preparation Program Characteristics Q125 Did you enter teaching through an alternative route to certification program? (An alternative route to certification program is a program that was designed to expedite the transition of nonteachers to a teaching career, for example, a state, district, or university alternative route to certification program.) o Yes (23) o No (24) Display This Question: If Did you enter teaching through an alternative route to certification program? (A n alternative rou... = Yes Q126 Which Alternative route did you complete? o Teach For America (1) o Other (2) ________________________________________________

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303 Q127 Were you a part of any of the following programs? Check all that apply. d Brightest Teacher Scholarship Program (7) Florida Fund for Minority Teachers (8) Jacksonville Teacher Residency Program (5) University of North Florida Urban teacher Residency Program (6) M.I.S.T.E.R (Mentoring Instructing Students Toward Effecti ve Role Models) (4) Teacher Incentive Fund (TIF) in Orange County Public Schools (3) None of the above (2) Other (1) ________________________________________________ Q128 Before your first year of teaching, did you take any undergraduate or gradu ate education courses? (e.g. as an elective, minor, or major) o Yes (28) o No (29) Skip To: Q131 If Before your first year of teaching, did you take any undergraduate or graduate education courses?... = No

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304 Q129 Before your first year of teaching, which best describes the type of undergraduate or graduate education courses you took? General Education (1) Subject/Content Area Methods (2) Pedagogy Methods (3) History or Foundations of Education (4) Art or Music Education (6) Other (5) ___________ _____________________________________ Q130 Before your first year of teaching, did you take any undergraduate or graduate courses which taught you: Please check all that apply. Classroom management techniques (1) Lesson Planning (8) How to Assess Le arning (9) How to use student performance data to inform instruction (6) How to serve students from diverse economic backgrounds (7) How to serve students with special needs (5) How to teach students who are limited English proficient (LEP) or Engl ish language learners (ELLs (4) Page Break

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305 Q131 What was the duration of your teacher preparation program PRIOR to you becoming teacher of record? Please report duration in the box provided. o None (1) o Weeks (2) _________________________________ _______________ o Semesters (3) ________________________________________________ o Years (4) ________________________________________________ Q132 What was the duration of your teacher preparation program AFTER you became teacher of record? Please report duration in the box provided. o None (1) o Weeks (2) ________________________________________________ o Semesters (3) ________________________________________________ o Years (4) ________________________________________________ Q133 In your teacher educat ion program, were your methods/pedagogy courses designed especially for your content area? (As opposed to being generic in order to be applicable to multiple content areas) o Yes (23) o No (24)

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306 Q134 Did you proceed through your teacher education progra m with a specific group of other students (i.e., in a cohort)? o Yes (23) o No (24) Q135 What percentage of your teacher education courses did you take fully online? o 0% (1) o 1% 25% (2) o 26% 50% (3) o 51% 75% (4) o 76% 99% (5) o 100% (6) Q136 What percentage of your teacher education courses did you take in a hybrid format (part online and part face to face)? o 0% (1) o 1% 25% (2) o 26% 50% (3) o 51% 75% (11) o 76% 99% (12) o 100% (13)

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307 Q137 Did you have any student teaching (s ometimes called practice teaching or an internship) prior to becoming teacher of record? o Yes (23) o No (24) Skip To: Q140 If Did you have any student teaching (sometimes called practice teaching or an internship) prior to... = No Display This Question: If Did you have any student teaching (sometimes called practice teaching or an internship) prior to... = Yes Q138 In how many different classrooms did you student teach? o One (1) o Two (2) o Three or more (3) Display This Question: If Did you have any student teaching (sometimes called practice teaching or an internship) prior to... = Yes Q139 How long did your student teaching last? If you student taught in more than one classroom, report the total amount of time spent student teaching across all assignments. Mark (X) only one box o 4 weeks or less (1) o 5 7 weeks (2) o 8 11 weeks (3) o 12 weeks or more (4) Page Break

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308 Q140 In what content areas does the teaching certificate certify you to teach in THIS state? (If you are certified in more than one content area or grade ranges degree, information about additional areas and ranges will be asked later.) Department (1) Subject (2 ) Elementary Education (1) ... Other ~ Other (102) Q141 What is your grade range of certificate? o Early childhood, preschool, or at least one of grades K 5 (1) o At least one of grades 6 8 (2) o At least one of grades 9 12 (3) Q142 Are you certifie d to teach in any other content areas or grade ranges? o Yes (23) o No (24) Skip To: Q151 If Are you certified to teach in any other content areas or grade ranges? = No Display This Question: If Are you certified to teach in any other content areas or grade ranges? = Yes Q143 If yes, please record all ADDITIONAL content areas in which this certificate certifies you to teach Department (1) Subject (2) Elementary Education (1) ... Other ~ Other (102)

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309 Q144 If yes, please record all ADDITIONAL grade ranges in which this certificate certifies you to teach o Early childhood, preschool, or at least one of grades K 5 (1) o At least one of grades 6 8 (2) o A t least one of grades 9 12 (3) Q145 Are you certified to teach in any other content areas or grade ranges? o Yes (1) o No (2) Skip To: Q146 If Are you certified to teach in any other content areas or grade ranges? = Yes Skip To: Q151 If Are you cer tified to teach in any other content areas or grade ranges? = No Display This Question: If Are you certified to teach in any other content areas or grade ranges? = Yes Q146 If yes, please record ADDITIONAL content areas in which this certificate certif ies you to teach. Department (1) Subject (2) Elementary Education (1) ... Other ~ Other (102) Q147 If yes, please record ADDITIONAL grade ranges in which this certificate certifies you to teach. o Early childhood, preschool, or at least one of grades K 5 (1) o At least one of grades 6 8 (2) o At least one of grades 9 12 (3)

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310 Display This Question: If Are you certified to teach in any other content areas or grade ranges? = Yes Q148 Are you certified to in any other content areas or grade ranges? o Yes (1) o No (2) Skip To: Q151 If Are you certified to in any other content areas or grade ranges? = No Display This Question: If Are you certified to in any other content areas or grade ranges? = Yes Q149 If yes, please record ADDITIONAL content ar eas in which this certificate certifies you to teach. Department (1) Subject (2) Elementary Education (1) ... Other ~ Other (102) Q150 If yes, please record ADDITIONAL grade ranges in which this certificate certifies you to teach. o Early childhood, p reschool, or at least one of grades K 5 (1) o At least one of grades 6 8 (2) o At least one of grades 9 12 (3) Page Break

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311 Q151 At what age did you first begin teaching full time at the K 12 or comparable ungraded level? Please do NOT include time spent as a student teacher. ________________________________________________________________ time at the K 12 or comparable ungraded level? Please do NOT include time spent as a student teacher. ________________________________________________________________ Page Break

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312 End of Block: Teacher Preparation Program Characteristics Start of Block: Retention Q153 Do you plan on teaching the next school year? 0 Definitely yes () Q154 Why or why not? ________________________________________________________________ Q155 How long do you plan to remain in teaching? o As long as I am able (1) o Until I am eligible for retirement benefits from this job (2) o Until I am eligi ble for retirement benefits from a previous job (3) o Until I am eligible for Social Security benefits (4) o Until a specific life event occurs (e.g. parenthood, marriage, retirement of spouse or partner) (5) o Until a more desirable job opportunity comes along (6) o Definitely plan to leave as soon as I can (7) o Undecided at this time (8)

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313 Q156 Do you plan on teaching for the next 2 years? o Definitely yes (1) o Probably yes (2) o Might or might not (3) o Probably not (4) o Definitely not (5) Q15 7 Do you plan on remaining in the field of education? o Definitely yes (1) o Probably yes (2) o Might or might not (3) o Probably not (4) o Definitely not (5) Display This Question: If Do you plan on remaining in the field of education? = Might or mig ht not Or Do you plan on remaining in the field of education? = Probably not Or Do you plan on remaining in the field of education? = Definitely not Q158 In what field other than education do you plan on continuing you career? _________________________ _______________________________________ End of Block: Retention Start of Block: Future Contact

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314 Q187 Please list any additional comments here: ________________________________________________________________ Q159 As a researcher, I would love to follo w up with you in the future. If you are interested, please provide your email address. ________________________________________________________________ End of Block: Future Contact Start of Block: Thank you! Q160 Thank you so much for taking this survey and I hope you have a great day and remainder of the school year! ________________________________________________________________ End of Block: Thank you!

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315 LIST OF A merican Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for Educational and Psychological Testing. Ahwee, S., Chiappone, L., Cuevas, P., Galloway, F., Hart, J., Lones, J., Medina, A., Menendez, R., Pilonieta, P., Provenzo, E., Shook, A., Stephens, P., Syrquin, A, & Tate, B. (2004). The hidden and null curriculums: An experiment in collective educational biographies. Educational Studies, 35 (1), 25 Akar, E. O. (2012). M otivations of Turkish pre service teachers to choose teaching as a career. Australian Journal of Teacher Education, 37 (10), 67 Apple, M. (2013). Con In D. Flinders & S. Thornton (Eds.), The Curriculum Studies Reader Fou rth Edition (pp. 167 Aksu, M., Demir, C. E., Daloglu, A., Yildirim, S., & Kiraz, E. (2010). Who are the future teachers in Turkey? Characteristics of entering student teachers. International Journal of Educational Development 30 91 Ayers, W. (1993). To teach: The journey of a teacher Babbie, E. R. (2013). The basics of social research Bandura, A. (1994). Self efficacy. In V. S. Ramachaudran (Ed.), Encyclope dia of human behavior (Vol. 4, pp. 71 81). New York: Academic Press. Banks, J. A. (1995). Multicultural education and curriculum transformation. Journal of Negro Education 390 Bailyn and opportunities for study Balyer, A., & reasons. International Education Studies, 7 Bartholomew, S. R., Bullock, E. P., & Nadelson, L. S. (2018). A Route Less Traveled: Journal of Education and Training 5 (2), 12 Barzun, J. (1945). Teacher in America Beck, Bertholle, Mastering the Art of French Cooking. London: Cassell & Co. Belfield, C., & Levin, H. (2013). The cumulative costs of the opportunity gap. In P.L. Carter & K.G. Welner (Eds.), Closing the opportunity gap: What America must do to give every child an even chance (pp. 195

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316 Berger, J. L., & educators: a person oriented approach. Vocations and Learning 5 (3), 225 Berry, B. (2013). Good schools and teachers for all students: Dispelling myths, facing evidence, and pursuing the right strat egies. In Carter, P. L & Welner K. G. (Eds.), Closing the opportunity gap: What America must do to give every child an even chance (pp. 18 1 Blumenreich, M., & Gupta, A. (2015). The globalization of Teach for America: An analysis of the institutional discourses of Teach for America and Teach for India within local contexts. Teaching and Teacher Edu cation, 48 87 Boland, J. and Keane, E. 2011. The transformative potential of service/community based learning as a pedagogy for diversity and social justice in teacher education: A case study from Ireland. In (Eds) T. Murphy and J. Tan. Service lear ning and educating in challenging contexts: International perspectives London: Continuum Books. Bondy, E., & Ross, D. D. (2008). The teacher as warm demander. Educational Leadership 66 (1), 54 Bo ith Anthony Bourdain ( Interview by D. Sheff). Playboy Magazine Retrieved from https://www.playboy.com/read/the november 2011 playboy interview with anthony bourdain Bourdain, A. (2010 ). Medium raw: A bloody valentine to the world of food and the people who cook New York, NY: Ecco. Boyd, D., Grossman, P., Ing, M., Lankford, H., Loeb, S., & Wyckoff, J. (2011). The influence of school administrators on teacher retenti on decisions. American Educational Research Journal, 48 (2), 303 Brandmo, C., & Nesje, K. (2017). Factors motivating students to become secondary school t each ers. In H. M. Watt, P. W. Richardson, & K. Smith (Eds.), Global Perspectives on Teacher M otivation (pp. 95 Bransford, J., Darling Ham L. Darling Hammond & J. Bransford (Eds.), Preparing teachers for a changing world: What teachers should learn and be able to do (pp. 1 John Wiley & Bransford, J., Derry, S., Berliner, D., & Hammerness, K., (with Beckett, KL). (2005). In L. Darling Hammond & J. Bransford Eds.), Preparing teachers for a changing world: What teachers should l earn and be able to do (p p. 40 87). San Francisco, CA: John Wiley & Bruinsma, M., & Jansen, E. P. (2010). Is the motivation to become a teacher related to pre profession?. European Journal of Teacher Ed ucation, 33 (2), 185

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317 Brookhart, S. M., & Freeman, D. J. (1992). Characteristics of entering teacher candidates. Review of educational research, 62 (1), 37 Butler, R. (2012). Striving to connect: Extending an achievement goal approach to teacher motivation to include relational goals for teaching. Journal of Educational Psychology, 104 (3), 726 Butler, R. (2014). What teachers want to achieve and why it matters: An achievement goal approach to teacher motivation In P.W. Richardson S.A. K arabenick, & H.M. Wat t (Eds.) Teacher motivation: Theory and practice. (pp. 20 35 ). New York: Routledge. Butler, R. (2017). Why choose teaching and why does it matter? In H. M. Watt, P.W. Richardson, & K. Smith (Eds.). Global perspectives on teacher motiva tion (pp. 377 388). Cambridge: Butler, T. E. (2014). Teacher perceptions of a national alternative certification program's preparation process: Providing equitable student experiences (Doctoral Dissertation). Available from ProQue st Dissertations and Theses database. (UMI No. 3648417 ) Carter, S.B. (1989). Incentives and rewards to teaching. In D. Warren (Ed.), American teachers: Histories of a profession at work (p p. 49 62 Research Association. C arter, P. L & Welner, K. G. (2013). Achievement gaps arise from opportunity gaps. In P.L. Carter & K.G. Welner (Eds.), Closing the opportunity gap: What America must do to give every child an even chance (pp. 1 Chi ldren's Defense Fund The state of America's children yearbook 2014 Washington, D.C.: Author. Clark, V. L. P., & Creswell, J. W. (2010). Understanding research: A consumer's guide New Jersey: Merrill/Pearson Education Clifford, G. (1989). Ma n/woman/teacher: Gender, family, and career in American educational history. In D. Warren (Ed.), American teachers: Histories of a profession at work (pp. 293 343). New York: American Educational Research Association. Cochran Smith, M., Barnatt, J., La hann, R., Shakman, K., & Terrell, D. (2008). Teacher education for social justice: Critiquing the critiques. In W. Ayers, T. Qu inn, & D. Stovall (Eds.), Hand book of social justice in education (pp. 625 639). New York: Routledge. Cochran Smith, M. & Dudley Marling, C. (2013). Crossing the divide? Diversity issues in teacher education and special education: A response to Leah Wasburn Journal of Teacher Education, 64 (3), 279 Cochran Smith, M. & Zeichner, K. (2005) (Eds). Studying teacher educa tion New York: Routledge.

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318 Cohen, D. (1989). Practice and policy: Notes on the history of instruction. In D. Warren (Ed.), American teachers: Histories of a profession at work (pp. 393 407). New York: American Educational Research Association Conant J. (1963). The education of American teachers New York: McGraw Cornell University. (2011). Why Teach? Cornell University Physics Teacher Education Co alition. Retrieved from http://phystec.physics.cornell.edu/ content/physics teaching careers Creswell, J. W. (2014). A concise introduction to mixed methods research Thousand Oaks, California: N Cupoli, K. K. (2016). Predicting success in placement. Linkages between personality, participation in professional development and placement success of MBA students (Doctoral Dissertation). Available from ProQuest Dissertations a nd Theses database. (UMI No. 10906563) amico, D., Pawlewicz, R. J., Earley, P. M., & McGeehan, A. P. (2017). Where are all the Black teachers? Discrimination in the teacher labor market. Harvard Educational Review, 87 (1), 26 Dana, N. F., & Yendol H oppey, D. (2008). development: Coaching inquiry oriented learning communities Thousand Oaks, Dana, N. F. & Yendol Hoppey, D. (2009). r esearch: Learning to teach and teaching to learn through practitioner inquiry (2 nd ed.). Darling Solving the dilemmas of teacher supply, demand, and standards: How we can ensure a competent, ca ring, and qualified teacher for every child National Commission on Teaching & America's Future. Kutztown, PA: Kutztown Distribution Center. Darling Hammond, L. (2008). The case for university based education. In M. Cochran Smith, S. Feiman Nemser, D. J. M cIntyre, & K. E. Demers (Eds.), Handbook of research on teacher education: Enduring questions in changing contexts (pp. 333 346). New York: Darling Hammond, L. (2010). The flat world and education: How America's commitment to equity will determine our future Darling What it will take to close the opportunity gap. In P.L. Carter & K. G. Welner ( Eds.), Closing the opportunity gap:

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335 BIOGRAPHICAL SKETCH Natalie Rid gewell graduated with a PhD in curriculum and i nstruction, with a focus on social foundations of education, and curric ulum, teachi ng, and teacher education She is an e xperienced and energetic educator who possesses a Master of Arts in English l iterature with American literature and digital humanities concentrations from The University of Georgia, an advanced degree in Li brary and Information Science from The University of South Carolina, and a Bachelor of Arts in English, with minors in history a nd F rench, from Georgia College & State University. She is also a former high school English language a rts teacher and taught at Peach County High School in Fort V alley, Georgia. Additionally, she has taught at Georgia College & State University, the University of South Carolina, the University of Georgia, and the University hletic Academic Writing Cente r