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Engagement and Motivation in Learning

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Title:
Engagement and Motivation in Learning Perspectives of Middle School Agricultural Education Students
Physical Description:
1 online resource (151 p.)
Language:
english
Creator:
Young, Ashley N
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Agricultural Education and Communication
Committee Chair:
Barrick, R Kirby
Committee Members:
Myers, Brian E
Osborne, Edward Wayne

Subjects

Subjects / Keywords:
agricultural -- education -- engagement -- learning -- middle -- motivation
Agricultural Education and Communication -- Dissertations, Academic -- UF
Genre:
Agricultural Education and Communication thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
The purpose of this study was to ascertain the perspectives of middle school agricultural education students on engagement and motivation in learning. Descriptive research was used to identify middle school agricultural education students’ self-perceptions of motivation and engagement in learning. Correlational research was used to examine the relationship between students’ age, grade level, and gender (independent variables) and students’ self-perceptions of motivation and engagement in learning (dependent variable). Data were analyzed using 213 completed instruments received from students within the classrooms of six agricultural educators in North Florida. Majority of students were female, and a large portion of students were 13 years old and in the 8th grade. Students in this study tended to report higher scores in learning focus, lower scores in valuing, and higher scores in anxiety. Additionally, students tended to report higher scores in task management, lower scores in planning, and high scores in self-sabotage. Students in higher grade levels within this study tended to report slightly lower levels of self-belief, uncertain control, task management, valuing, and persistence. Additionally, students in higher grade levels within this study tended to report slightly higher levels of self-sabotage and disengagement. Older students within the study tended to report slightly higher levels of self-sabotage and uncertain control. Males within the study tended to report slightly higher levels of disengagement and females tended to report slightly higher levels of anxiety and learning focus. Based on the findings of this study recommendations on ways to increase students’ valuing, planning, self-belief, task management, and persistence, as well as ways to decrease anxiety, self-sabotage, uncertain control, and disengagement, were made to the educators who participated in this study.
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.
Statement of Responsibility:
by Ashley N Young.
Thesis:
Thesis (M.S.)--University of Florida, 2013.
Local:
Adviser: Barrick, R Kirby.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0045984:00001

MISSING IMAGE

Material Information

Title:
Engagement and Motivation in Learning Perspectives of Middle School Agricultural Education Students
Physical Description:
1 online resource (151 p.)
Language:
english
Creator:
Young, Ashley N
Publisher:
University of Florida
Place of Publication:
Gainesville, Fla.
Publication Date:

Thesis/Dissertation Information

Degree:
Master's ( M.S.)
Degree Grantor:
University of Florida
Degree Disciplines:
Agricultural Education and Communication
Committee Chair:
Barrick, R Kirby
Committee Members:
Myers, Brian E
Osborne, Edward Wayne

Subjects

Subjects / Keywords:
agricultural -- education -- engagement -- learning -- middle -- motivation
Agricultural Education and Communication -- Dissertations, Academic -- UF
Genre:
Agricultural Education and Communication thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract:
The purpose of this study was to ascertain the perspectives of middle school agricultural education students on engagement and motivation in learning. Descriptive research was used to identify middle school agricultural education students’ self-perceptions of motivation and engagement in learning. Correlational research was used to examine the relationship between students’ age, grade level, and gender (independent variables) and students’ self-perceptions of motivation and engagement in learning (dependent variable). Data were analyzed using 213 completed instruments received from students within the classrooms of six agricultural educators in North Florida. Majority of students were female, and a large portion of students were 13 years old and in the 8th grade. Students in this study tended to report higher scores in learning focus, lower scores in valuing, and higher scores in anxiety. Additionally, students tended to report higher scores in task management, lower scores in planning, and high scores in self-sabotage. Students in higher grade levels within this study tended to report slightly lower levels of self-belief, uncertain control, task management, valuing, and persistence. Additionally, students in higher grade levels within this study tended to report slightly higher levels of self-sabotage and disengagement. Older students within the study tended to report slightly higher levels of self-sabotage and uncertain control. Males within the study tended to report slightly higher levels of disengagement and females tended to report slightly higher levels of anxiety and learning focus. Based on the findings of this study recommendations on ways to increase students’ valuing, planning, self-belief, task management, and persistence, as well as ways to decrease anxiety, self-sabotage, uncertain control, and disengagement, were made to the educators who participated in this study.
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.
Statement of Responsibility:
by Ashley N Young.
Thesis:
Thesis (M.S.)--University of Florida, 2013.
Local:
Adviser: Barrick, R Kirby.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
lcc - LD1780 2013
System ID:
UFE0045984:00001


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1 ENGAG E MENT AND MOTIVATION IN LEARNING: PERSPECTIVES OF MIDDLE SCHOOL AGRICULTURAL EDUCATION STUDENTS By ASHLEY YOUNG A THE SIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQU IREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2013

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2 2013 Ashley Young

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3 To my mom and dad F or their constant love, support, and encouragement which has molded me into the person I am today.

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4 ACKNOWLEDGMENTS First and for emost I must thank my parents for the constant love and support which has allowed me to achieve my successes in life. First, I must thank my mom, Cheryl Young, for being my backbone. She has been the one person that I have always been able to count on for an ear to listen and helping hands to get the job done. Next, I must thank my dad, Mark Young, for his constant encouragement and support throughout my academic career. He was often the person I could go to for advice and assistance with my academics. Last but not least, I must thank all of my grandparents for t heir constant love and support. I t examples in life that I had instilled within me the values of a hard work ethic and determination Next I must thank the ma ny educators in my life who have encouraged and motivated me throughout the years. I am most grateful to my h igh school agricultural teacher, Mrs. Nyree Washington for instilling a love of agriculture and a love of education within me As an ag ricult ural educator myself I now often look back at the e xperiences I had in high school and feel grateful to have had a role model for my career who was as passion ate and self serving as she was I f eel blessed to be able to say I have earned two degrees from the Un iver sity of Florida, which could not have been possible without the support and guidance of all of the faculty and staff members in the Agricultural Education and Communication D epartment. I owe a great deal of gratitude to my advisor Dr. Kirby Barrick f or his guidance and support throughout the planning, researching, and writing of my thesis. I must also thank my committee members Dr. Ed Osborne for his help in develop ing my writing skills and for helping to edit and draft my study and Dr. Brian Myers f or continuing to push me to think outside of the box. I must also thank Dr. Myers and his

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5 wife Margaret for shari ng their son Tim as a student and FFA member, and for all of their help within my classroom and FFA chapter at High Springs Community School. I must also thank Dr. Chris Estepp, Dr. Christopher Stripling, Dr. Kate Shoulders and Dr. Andrew Thoron for their guidance and mentoring through both of my degrees Lastly, I must thank Sarah Burleson for being the best friend a girl could ask for and for always lending an ear to listen and a mind for brain storming. help and support that guided me throughout the process of writing this thesis. Finally, I must thank my students, colleagues, and the parents at High Springs Community School. My colleagues have been supportive of me while balancing teaching and working tow and they are the best group of people to work with. I must also thank my students for assuring me that teaching is my passion in life and for c ontinuing to motivate and inspire me every day I feel beyond blessed to have be en able to continue my education and earn a degree from the University of Florida It is due to the love, support, and guidance of all of the people I have mentioned t hat earning this degree was possible. As serving as role models and for raising me to be the woman that I am today.

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6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 LIST OF FIGURES ................................ ................................ ................................ ........ 12 LIST OF ABBREVIATIONS ................................ ................................ ........................... 13 ABSTRACT ................................ ................................ ................................ ................... 14 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 16 Statement of the Problem ................................ ................................ ....................... 22 Purpose and Objectives ................................ ................................ .......................... 24 Significance of Study ................................ ................................ .............................. 24 Definitions of Terms ................................ ................................ ................................ 25 Limitations of the Study ................................ ................................ ........................... 28 Basic Assumptions ................................ ................................ ................................ 28 Chapter Summary ................................ ................................ ................................ ... 29 2 REVIEW OF LITERATURE ................................ ................................ .................... 31 Agricultural Education ................................ ................................ ............................. 31 Student Dropout ................................ ................................ ................................ ...... 33 Social Consequences of Dropout ................................ ................................ ..... 33 Individual Consequences of Dropout ................................ ................................ 34 Preventing Dropout ................................ ................................ .......................... 35 Cognitive Development of Adolescents ................................ ................................ .. 36 Theory of Cognitive Development ................................ ....................... 36 Sensorimotor intelligence ................................ ................................ ........... 38 Preoperational intelligence ................................ ................................ ......... 38 Concrete operational intelligence ................................ ............................... 38 Formal operational intelligence ................................ ................................ .. 39 Cognitive Development an d Middle School Students ................................ ....... 39 ................................ ........................ 40 Oral sensory stage ................................ ................................ ..................... 41 Muscular anal stage ................................ ................................ ................... 41 Locomotor genital stage ................................ ................................ ............ 41 Latency ................................ ................................ ................................ ...... 41 Puberty and adolescence ................................ ................................ .......... 42 Young adulthood ................................ ................................ ........................ 42 Adulthood ................................ ................................ ................................ ... 43

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7 Maturity ................................ ................................ ................................ ...... 43 Motivation ................................ ................................ ................................ ............... 43 Expectancy Value Theory of Motivation ................................ ........................... 44 Self Determination Theory of Motivation ................................ .......................... 46 Achievement Goal Theory of Motivation ................................ .......................... 46 Motivational Behaviors over Time ................................ ................................ .... 46 Engagement ................................ ................................ ................................ ........... 47 Behavioral Engagement ................................ ................................ ................... 49 Cognitive E ngagement ................................ ................................ ..................... 49 Emotional Engagement ................................ ................................ .................... 50 How do Learners Become Engaged? ................................ ............................... 50 Interaction ................................ ................................ ................................ .. 51 Exploration ................................ ................................ ................................ 51 Relevancy ................................ ................................ ................................ .. 51 Multimedia an d Instruction ................................ ................................ ......... 52 Motivation and Engagement ................................ ................................ ................... 52 The Motivation and Engagement Wheel ................................ ................................ 54 Self Efficacy and Expectancy Value Theory ................................ ..................... 55 Attribution Theory and Control ................................ ................................ .......... 55 Goal orientation and self re gulation ................................ ................................ .. 56 Need achievement and self worth motivation theory ................................ ........ 56 Empirical Research ................................ ................................ ................................ 57 Dolezel ................................ ................................ ................................ ............. 57 Turner and Herren ................................ ................................ ............................ 59 Rohs and Anderson ................................ ................................ .......................... 60 Martin ................................ ................................ ................................ ............... 61 Conceptual Model of Engagement and Motivation ................................ ................. 62 Student Attributes ................................ ................................ ............................. 63 Gender ................................ ................................ ................................ ....... 63 Age ................................ ................................ ................................ ............ 64 Grade level ................................ ................................ ................................ 64 Env ironmental Attributes ................................ ................................ .................. 64 Home influences ................................ ................................ ........................ 64 Institutional influences ................................ ................................ ................ 6 5 Student Development ................................ ................................ ....................... 67 Chapter Summary ................................ ................................ ................................ ... 69 3 METHODOLOGY ................................ ................................ ................................ ... 70 Research Design ................................ ................................ ................................ .... 70 Validity of the Research Design ................................ ................................ ....... 71 Internal Validity ................................ ................................ ................................ 71 External Validity ................................ ................................ ................................ 73 Construct Validity ................................ ................................ ............................. 73 Statistical Conclusion Validity ................................ ................................ ........... 74 Population ................................ ................................ ................................ ............... 74 Instrumentation ................................ ................................ ................................ ....... 75

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8 Data Collection ................................ ................................ ................................ ....... 77 Data Analysis ................................ ................................ ................................ .......... 77 Research Objective One ................................ ................................ .................. 78 Research Objective Two ................................ ................................ .................. 80 Research Objective Three ................................ ................................ ................ 82 Chapter Summary ................................ ................................ ................................ ... 83 4 RESULTS ................................ ................................ ................................ ............... 84 Response Rates ................................ ................................ ................................ ..... 85 Post Hoc Reliability of Instruments ................................ ................................ ......... 85 Description of Population ................................ ................................ ........................ 85 Gender ................................ ................................ ................................ ............. 86 Age ................................ ................................ ................................ ................... 86 Grade Level ................................ ................................ ................................ ...... 86 Objective One ................................ ................................ ................................ ......... 87 Objective Two ................................ ................................ ................................ ......... 96 Objective Three ................................ ................................ ................................ .... 105 Sum mary ................................ ................................ ................................ .............. 109 5 SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ................................ 110 Objectives ................................ ................................ ................................ ............. 110 Summary of Findings and Conclusions ................................ ................................ 110 Description of Population ................................ ................................ ................ 110 Objective One ................................ ................................ ................................ 111 Objective Two ................................ ................................ ................................ 113 Objective Three ................................ ................................ .............................. 114 Discussion and Implications ................................ ................................ .................. 116 Objective One reported perceptions of motivation to learn. ................................ ................ 116 Objective Two Identify middle reported perceptions of engagement in learning. ................................ ........ 121 Objective Three Examine the relationships between middle school agricultural education students gender, and grade level), and their perceptions of motivation to learn and engagement in learning. ................................ ................................ .............. 125 Recommendation for Practitioners ................................ ................................ ........ 129 Recommendations for Further Research ................................ .............................. 137 APPENDIX A INVITATION TO TEACHE RS ................................ ................................ ............... 138 B MOTIVATION AND ENGAGMENT SCALE ................................ .......................... 139 C ADMINISTRATION PROTOCOL ................................ ................................ .......... 141

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9 D IRB APPROVAL ................................ ................................ ................................ ... 143 E IRB PARENTAL CONSENT ................................ ................................ ................. 144 F IRB STUDENT CONSENT ................................ ................................ ................... 145 LIST OF REFERENCES ................................ ................................ ............................. 146 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 150

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10 LIST OF TABLES Table page 2 1 ................................ ...... 37 2 2 ................................ .......................... 40 4 1 Descriptive Statistics of the Sample ( n = 213) ................................ .................... 86 4 2 Adaptive and Maladaptive Motivation Construct Means ( n = 213) ...................... 87 4 3 Adaptive and Maladaptive Motivation Construct Age Means .............................. 89 4 4 Adaptive and Maladaptive Motivation Construct Grade Level Means ................. 91 4 5 Adaptive and Maladaptive Motivation Construct Gender Means ........................ 92 4 6 Adaptive and Maladaptive Global Motivation Construct Means ( n = 213) .......... 93 4 7 Adaptive and Maladaptive Global Motivation Construct Age Means .................. 94 4 8 Adaptive and Maladaptive Global Motivation Construct Grade Level Means ..... 95 4 9 Adaptive and Maladaptive Global Motivation Construct Gender Means ............. 96 4 10 Adaptive and Maladaptive Engagement Construct Means ( n = 213) .................. 97 4 11 Adaptive and Maladaptive Engagement Construct Age Means .......................... 98 4 12 Adaptive an d Maladaptive Engagement Construct Grade Level Means ........... 100 4 13 Adaptive and Maladaptive Engagement Construct G ender Means .................. 101 4 14 Adaptive and Maladaptive Global Engagement Construct Means ( n = 213) .... 102 4 15 Adaptive and Maladaptive Global Engagement Construct Age Means ............ 103 4 16 Adaptive and Maladaptive Global Engagement Construct Grade Level M eans 104 4 17 Adaptive and Maladaptive Global Engagement Construct Gender Means ....... 104 4 18 Correlations Among Global Motivation/Engagement Mean Construct Scores and Age/Grade Level ( n = 213) ................................ ................................ ........ 107 4 19 Correlations Among Global Motivation/En gagement Mean Construct Scores and Gender ( n = 213) ................................ ................................ ....................... 107

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11 4 20 Correlations Among Adaptive/Maladaptive Motivation/Engagement Mean Construct Scores and Age/Grade Level ( n = 213) ................................ ............ 108 4 21 Correlations Among Adaptive/Maladaptive Motivation/Engagement Mean Construct Scores and Gender ( n = 213) ................................ ........................... 108

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12 LIST OF FIGURES Figure page 1 1 Significance of Motivation and Engagement on Student Achievement ............... 23 2 1 Agricultural Education Progra m ................................ ................................ .......... 32 2 2 The Motivation and Engag ement Whee l ................................ ............................. 53 2 3 A Conceptual Model for Motivation and E ngagement ................................ ......... 68

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13 LIST OF ABBREVIATION S CMP Civic Marshall Plan FFA The National FFA Organization IRB Institutional Review Board MES Motivation and Engagement Scale MES JS Motivation and Engagement Scale Junior S chool MEW Motivation and Engagement Wheel NAEP National Assessment of Educational Progress NCLB No Child Left Behind Act SAE Supervised Agricultural Experience U.S. United States USDE U.S. Department of Education

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14 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ENGAGEMENT AND MOTIVATION IN LEARNING: PERSPECTIVES OF MIDDLE SCHOOL AGRICULTURAL EDUCATION STUDENTS By Ashley Yo ung August 2013 Chair: Kirby Barrick Major: Agricultural Education and Communication The purpose of this study was to ascertain the perspectives of middle school agricultural education students on engagement and motivation in learning. D escriptive rese arch was used to identify middle school agricultural education students self perceptions of motiva tion and engagement in learning. C orrelational research was used (independent vari able s ) perceptions of motivation and engagement in learning (dependent variable) Data were analyzed using 213 completed instruments received from students within the classrooms of six agricultural educators in North Florida. Majority o f students were female, and a large portion of students were 13 years old and in the 8 th grade Studen ts in this study tended to report higher scores in learning focus, lower scores in valuing, and higher scores in anxiety. Additionally, students t ended to report higher scores in task management, lower scores in planning, and high scores in self sabotage. S tudents in higher grade levels within this study tended to report slightly lower levels of self belief, uncertain control, task management, valuing, and persistence. Additionally, students in higher grade levels within this study tended to

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15 report slightly higher levels of self sabotage and disengagement. Older students within the study tended to report slightly higher levels of self sabotage and uncertain control. Males within the study tended to report slightly higher levels of disengagement and females tended to report slightly higher levels of anxiety and learning focus. Based on luing, planning, self belief, task management, and persistence, as well as ways to decrease anxiety, self sabotage, uncertain control, and disengagement were made to the educators who participated in this study

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16 CHAPTER 1 INTRODUCTION dropout crisis in the United States claims more than one million students each year, costing individuals the loss of potential earnings and the nation hundreds of billions of dollars in lost revenue, lower economic activity and increased Balfanz, Bridgeland, Bruce, & Horning Fox, 2012, p.5). This was how the Civic Enterprises Everyone Graduates Center at Johns Hopkins University began its annual update of the Building a Grad Nation: Progress and Challenge in Ending the High School Dropout Epidemic report. The dropout crisis in the United States affects national scale the dropout crisis affects every U.S. citizen. The Civic Enterprises Everyone Graduate s Center (2012) indicated that by graduating half of one class of dropouts the U.S. taxpayer would save $45 billio n dollars in that single year. According to the U.S. Department of Education (USDE) report, Trends in High School Dropout and Completion Rates in the United States: 1972 2009 the average high school dropout costs the U.S. economy roughly $240,000 over his or her lifetime in lower tax contributions, higher criminal activity, and higher dependence on programs such as Medicaid, Medicare, and welfa re (U.S. Department of Education, 2009, p.1). The Civic Enterprises Everyone Graduates Center (2012) argued that raising educational achievement translates to higher wages and social mobility for individuals, thus improving economic returns through increa sed revenues from productive workers. Education has been accredited for the productivity growth of the United States between the 1950s and 1990s. By continuing to improve educ ation more jobs will be created,

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17 and the workforce will have the power to grow th e economy through a boost in gross domestic products ( Civic Enterprises Everyone Graduates Center, 2012 ). According to the annual update of the Building a Grad Nation: Progress and Challenge in Ending the High School Dropout Epidemic ng high and fast changing economy demands workers who are knowledgeable, can synthesize an d evaluate information, think critically, and solve problems (Fredicks, Bluenfield & last forty years. In 1973, 73% of all U.S. jobs only required a high school diploma, w hereas the workforce of this decade and future decades will require not only completing high school but also attaining some college or post secondary training ( Civic Enterprises Everyone Graduates Center, 2012 ). In March of 2010 a union of U.S. organizati ons joined to develop the Civic Marshall Plan (CMP) to end the dropout crisis in the United States ( Civic Enterprises Everyone Graduates Center, 2012 ). The CMP created two clear goals ( Civic Enterprises Everyone Graduates Center, 2012) : A 90 percent natio nwide high school graduation rate for the class of 2020 (at 75.5 percent for the class of 2009, ~ 1.3 percent point increase per year is needed through 2020); and The highest college attainment rates in the world, with at least six in ten students earning a college degree by 2020 (up from three in ten today) (p.20). To address these goals the CMP leadership council developed a phased approach with clear benchmarks for the years ahead that focused on all levels of education, beginning with elementary school s and working through middle and high schools ( Civic

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18 Enterprises Everyone Graduates Center, 2012 ). While the national graduation rate is currently at 75 percent, the rate of improvement has not been occurring fast enough to achieve the goal of a 90 percent national graduation rate by the class of 2020 ( Civic Enterprises Everyone Graduates Center, 2012 ). As a result, attention and investments at all levels including local, state, and federal have been called for to address the high school dropout crisis ( Civic Enterprises Everyone Graduates Center, 2012). Approaches to decreasing high school dropout rates have focused on raising educational achievements at all levels and ages of education. The Bush administration acknowledged a gap in student achievement within U.S. secondary schools and formul ated a means for intervention. In 2002, the Elementary and Secondary Education Act of o close the achievement gap with accountability, flexibility, and c hoice, so that no child wa s l eft Public Law 107 110 2002, 115 STAT 1425). The No Child Left Behind Act (2002) was designed with the purpose to ensure that all children have a fair, equal, and significant opportunity to obtain a high quality educa tion and reach, at a minimum, proficiency on challenging state academic achievement standards and state academic assessments (Public Law 107 110, 2002, 115 STAT. 1439). The Act outlined numerous objectives in order to accomplish the purpose, including: (1) high quality academic assessments, curriculum, and instructional materials be aligned with challenging state academic standards, in order to measure progress against common expectations for student academic achievement ; (2) meeting the educational nee ds of low achieving children poverty schools, limited English proficient children, migratory children, children with disabilities, Indian children, neglected or delinquent children, and young children in need of reading assistance; ( 3) closing the achievement gap between high and low performing children; (4) and holding schools, local educational agencies, and states accountable for improving the academic achievement of all students (Public Law 107 110, 2002, 115 STAT. 1439 1440).

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19 Conversely, the National Assessment of Educational Progress (NAEP) reported no significant difference in assessment reading scores in 2008; no significant change from 2004 to 2008 for 13 year old students in mathematic assessment scores; and no measurable changes in science assessment scores from 1996 to 2005 for 8 th grade students (National Center for Educational Statistics 2010). Newmann, Wehlage, and Lamborn (1992) indicated the most urgent and continuing issue for students and teache rs has not been lo w achievement but student disengagement. Moreover, low achievement levels have been attributed to low student motivation and engagement in learning (Fredricks et al., 2004). Newman et al. (1992) has argued that efforts must be focused on learning how to en gage students in order to enhance achievement. Over the past decade research has shown academic engagement as a key factor to student success in school, as it predicts learning, grades, achievement test scores, attendance patterns, student retention, acade mic resilience, and graduation rates (Skinner, Furrer, Marchand, & Kindermann, 2008). Therefore, an investigation of student engagement is the most local approach to close gaps in student achievement and develop interventions to decrease school dropout rat es (Appleton, Christenson, Kim, & Reschly, 2006). Appleton et al. (2006) noted that although interest in engagement has exponentially amplified in recent years, the distinction between motivation and engagement remains a matter of debate. Engagement has b p.428 ), while given behavior (Appleton et

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20 al., 2006 p.428 ). Furthermore, motivation has been stated to underpin student achievement (Martin, 2003). Therefore, motivation and engagement have been suggested as separate but cohesive constructs (Appleton et al., 2006). Mo engage, learn, work effectively, and achieve potential at school and have been argued Mark s (2000) noted that student engagement leads to achievement and contributes to and Kaplan engages in classroom learning tasks. Marks (2000) argued that students who are engaged in the classroom will be more likely to learn, view classroom experiences as rewarding, graduate from school, and pursue higher education. Research has shown a variety of indica of instruction, relationships with teachers, parental attitudes and expectations, peers, the classroom learning environment, structure and culture of the school, and socio demographic status, gender, and age of the student (Martin, 2008). Efforts to increase student engagement arose in the mid 1980s and have been a theme in school reforms over the past three decades (Marks, 2000; Taylor & Parsons, 2011). Today, schools have consistentl y faced the issue of student disengagement due to an increased cultural diversity in the student body, large portions of students with emotional investments (Newmann et a l., 1992). The challenge for students in schools today has been the ability to cope with high demands of the teacher while avoiding

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21 boredom, maintaining self respect, and aiming to succeed in school (Newmann et al., 1992). At the same time, teachers have b een faced with the challenge of encouraging students to do academic work while taking it seriously enough to learn (Newmann et al., 1992). Additionally, a lack of student engagement has been attributed to factors of school characteristics including curricu lum fragmentation, weak instruction, and low expectations for learning (Marks, 2000). A call for reform in all school levels has been prevalent in research, yet a call on schools serving early adolescents has been especially strong (Lee & Smith, 1993). M iddle school students continue to be underperformers in the U.S. educ ational system (Balfanz, Herzog & Iver, 2007). While steep declines of motivation have been seen rec orded to steadily decline following the transition from elementary to middle school (Jang, 2008). Jang (2008) indicated that as students transition through levels of school workloads and difficulty of work increase, grading becomes more rigorous, and instr uction becomes less personalized. Consequently, a steady decline in engagement has been documented to start in kindergarten and extend through graduation (or dropout), particularly during the transition to middle or high school (Skinner et al., 2008; Taylo r & Parsons, 2011). In point of fact, U.S. Secretary of Education Arne Duncan 12 Civic Enterprises Everyone Graduates Center, 2 012 p.8). According to Balfanz et al. (2007) signs of behavioral and emotional disengagement are most prevalent in adolescent children. Early adolescence has been

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22 noted as an instrumental phase in terms of creating changes in student achievement beliefs a nd behaviors (Ryan & Patrick, 2001). Therefore, focusing on addressing student disengagement within adolescents will provide the most impact on the development of students (Lee & Smith, 1993). Nevertheless, current reform efforts have focused on improving instructional curriculum and improving the responsibilities, capabilities, and views of teachers and administrators (Balfanz et al., 2007). To address student achievement gaps and the high school dropout epidemic within the U.S. secondary school system r esearch must begin with further investigation into the viewpoints of middle school students on engagement and motivation in learning. Statement of the Problem The problem of lagging increased graduation rates, disappointing achievement levels, and lack o f engagement and motivation in adolescents has been facing the U.S. secondary school system for decades (Appleton et al., 2006; Baifanz et al., 2012; Fredicks et al., 2004; Lee & Smith, 1993; Jang, 2008; Marks, 2000; Skinner et al., 2008). Currently, almos t one in four Americans do not complete high school with their graduating class, and while dropout rates in the U.S. have been decreasing, reports have shown rates are not decreasing fast enough to meet the goal of a 90 percent national graduation rate by the class of 2020 (Baifanz et al., 2012). Low levels of engagement have been reported in U.S. schools over the past three decades, and chronic disengagement has been noted to affect forty to sixty percent of secondary schools (Marks, 2000). Additionally, a need for all learners to be actively and emotionally engaged in learning was called for by the National Research Agenda

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23 (Doerfert, 2011) in the Research Priority Area of Meaningful, Engaged Learning in All Environments. Dropping out of school has been kn own as a continuous process which does not occur overnight, thus student engagement and motivation have been noted as methods for intervening when early signs of disconnect in learning are recognized (Appleton et al., 2006). Ryan and Patrick (2001) noted t hat adolescence has been the most effective stage to create impactful learning gains in achievement and motivation. However, current reform methods have focused primarily on school teachers and administrators (Balfanz et al., 2007). Therefore, an investiga tion into the perspectives of students is essential to understanding the trend of disengagement and motivation in learning (F igure 1 1). Figure 1 1 Significance of Motivation and Engagement on Student Achievement

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24 Purpose and Objectives The purpose o f the study was to ascertain the perspectives of middle school agricultural education students on engagement and motivation in learning. This study aimed to address the following objectives: 1) rep orted perceptions of motivation to learn, 2) reported perceptions of engagement in learning, 3) Examine the relationships between middle school agricultural education demographic characteri stics ( age, gender and grade level), and their perceptions of motivation to learn and engagement in learning. Significance of Study The inferences gathered from this study provide several promises of significance for all stakeholders of the U.S. seconda Rumberger (1987) indicated that student dropout should be examined as a process of disengagement from school, and that the means for impl ementation of effectual interventions can be developed by identifying probable dropouts at an early age (Rumberger, 1987). Literature on motivation and engagement to date has been conceptualized in numerous studies (Fredricks et al., 2004). In spite of tha t, a shortage exist s tivation in learning. Additionally, knowledge attained from this study will assist teachers and school

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25 Educators will be able to use the conclusions of this study to incre ase student engagement by transforming teaching methods to include strategies which will motivate students to engage in academic activities (Jang, 2008). As a result, teachers will improve student success, as success has been noted to be determined by the extent to which students engage in learning tasks (Patrick et al., 2007). Thus, teachers and administrators will be closer to closing the gap between high achieving and low achieving students and meeting objectives mandated by the No Child Left Behind Act ( Public Law 107 110 2002). Lastly, engagement and motivation in learning may be a solution to the broader conundrum of preventing student dropout and meeting the high demands of a globally changing workforce. Definitions of Terms 1. Achievement the qualit y and quantity of a student's work motivation and engagement level in learning (Martin, 2007). 2. Adaptive B ehaviors (Martin, 2012 ). In th is study adaptive behaviors were operationally defined as persistence, planning, and task management, which were found in the Engagement and Motivation Scale (Martin, 2009). 3. Adaptive C ognitions (Martin, 2012) In this study adaptive c ognitions were operationally defined as self efficacy, mastery orientation, and valuing, which were found in the Engagement and Motivation Scale (Martin, 2009). 4. Agricultural Education teaching and l 5. Age the time of life at which some particular qualification, power, or capacity arises or rests age was operationalized as 11, 12, 13, 14 15, and 16 years old 6. Anxiety uneasy or sick feeling students get when they think about their school or university work or tasks. Worrying is their fear of not doing very well in their 805). In this study, anxiety was

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26 operationalized by the maladaptive engagement construct found on the Engagement and Motivation Scale (Martin, 2009). 7. Autonomy self directing freedom, especially moral inde autonomy wa s operationalized by adaptive and maladaptive cognitions constructs found in the Engagement and Motivation Scale (Martin, 2009). 8. Belonging close or intimate relationship W this study, belonging was operationalized by adaptive and maladaptive cognitions constructs found in the Engagement and Motivation Scale (Martin, 2009). 9. Competence the knowledge that enables a person to speak and understan d a Merriam operationalized by adaptive and maladaptive cognitions constructs found in the Engagement and Motivation Scale (Martin, 2009). 10. Disengagement are at risk of giving up at was operationalized by the maladaptive cognitive construct found on the Engagement and Motivation Scale (Martin, 2009). 11. Engagement 28). In this study, engagement wa s operationalized by adaptive and maladaptive engagement constructs found in the Engagement and Motivation Scale (Martin, 2009). 12. F ailure Avoidance 2009, p. 805). In this study, failure avoidance was operationalized by the maladaptive cognition cons truct found on the Engagement and Motivation Scale (Martin, 2009). 13. Gender the behavioral, cultural, or psychological traits typically associated with operationalized as male or fema le. 14. Global Booster Behavior 15. Global Booster Thought belief, valuing, and learning focus 16. Global Guzzler he average of self (Martin, 2012, p.17).

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27 17. Global Muffler 18. Grade Level a class organized for the work of a particular year of a school operationalized as sixth, seventh, or eighth grade. 19. Learning focus this study learning focus was operationally defined by the adaptive engagement constructs found in the Motivation and Engagement Scale (Martin, 2009). 20. Maladaptive Behaviors (Martin, 2012) In this study negative behaviors were operat ionally defined as self handicapping and disengagement, which were found in the Engagement and Motivation Scale (Martin, 2009). 21. Maladaptive Cognitions (Martin, 2012) In this study negative cognitions were operationally defined as anx iety, failure avoidance, and uncertain control, which were found in the Engagement and Motivation Scale (Martin, 2009). 22. Mastery Orientation In this study, mastery orientation was operationalized by the adaptive cognitions construct found in the Engagement and Motivation Scale (Martin, 2009). 23. Middle School Merriam ctionary (n.d.). In this study, middle school was operationalized as including students in grades six, seven, and eight. 24. Motivation is regard, motivation is related to underlying psychological processes including, autonomy, belonging, and competence (Appleton et al., 2006, p.428). In this study, motivation is operationalized by adaptive and maladaptive cognitions constructs found in th e Engagement and Motivation Scale (Martin, 2009). 25. Planning of their progress as they are doing it (Martin, 2009, p.804). In this study, planning was operationalized by the adaptive engage ment construct found in the Engagement and Motivation Scale (Martin, 2009). 26. Persistence 2009, p.804). In this study, persistence was operationalized by the adaptive engagement construct of the Engagement and Motivation Scale (Martin, 2009).

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28 27. Self belief f and confidence in their ability to understand or to do well in their school or universit y work, to meet challenges they face, and to perform to their best of their ability (Martin, 2009, p.804). In this study, self belief was operationalized by the adaptive cognitions construct found in the Engagement and Motivation Scale (Martin, 2009). 28. Sel f sabotage 9, p.805). In this study, self sabotage was operationalized by the maladaptive engagement construction found in the Engagement and Motivation Scale (Mart in, 2009). 29. Task Management timetables, and choose and arrange where they prepare for school or university management was operationalized by the adaptive engagement construct found in the Engagement and Motivation Scale (Martin, 2009). 30. Valuing p.804). In this study, valuing was operationalized by the adaptive cognitions construct found in the Engagement and Motivation Scale (Martin, 2009). 31. Uncertain Control artin, 2009, p.805). In this study, uncertain control was operationalized by the maladaptive cognitions construction found in the Engagement and Motivation Scale (Martin, 2009). Limitations of the Study The inferences gathered from this investigation were subject to the following limitations: 1) The data collected during this investigation included perceptions and beliefs of individual adolescents in terms of motivation and engagement. 2) Data were collected from middle school agricultural education students i n six selected middle schools within Florida ; therefore, generalizability is limited to areas with similar demographics and characteristics specific to the sampling frame. 3) engagement a nd motivation at the time they completed the instrument. Basic Assumptions The assumptions of this study were that all participants responded in a truthful manner and put forth authentic effort into reading, understanding, and answering the

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29 questions fou nd on the instrument. In addition, the Engagement and Motivation Scale has been previously used with middle school students and was assumed to be a valid and reliable instrument for the middle school students who participated in this study. Chapter Summar y Low levels of student achievement and the current high school dropout epidemic economy ( Civic Enterprises Everyone Graduates Center, 2012), but also a threat to the future workforce of our country, as they will be demanded to not on ly obtain a high school diploma but also some college or postsecondary training in order to compete in the globally competitive market ( Civic Enterprises Everyone Graduates Center 2012; Fredicks, Bluenfield & Paris, 2004). Research has indicated that inc reasing graduation rates among students can be achieved through raising student achievement leve ls (Civic Enterprises Everyone Graduates Center 2012), and that student achievement can be enhanced by focusing on the constructs of student engagement and motivation (Appleton et al., 2006; Newmann et al., 1992; Skinner et al., 2006). Also, a focus is required on adolescent children in order to create the most significant changes in towards engagement and motivation ( Civic Enterprises Everyone Graduates Center, 2012; Balfanz, Herzog & Iver, 2007; Jang, 2008; Lee & Smith, 1993; Skinner et al., 2008; Taylor & Parsons, 2011). The National Research Agenda (Doefert, 2011) recognized the ne cessity for increasing student engagement and motivation in secondary school systems by calling for all learners to be actively and emotionally engaged in learning in the Research Priority Area of Meaningful, Engaged Learning in All Environments.

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30 This stu dy aimed to meet the priorities of the National Research Agenda and the concerns of student achievement and graduation rates by ascertaining the perspectives of middle school students on motivation and engagement in learning. Conclusions gathered in this s tudy will add information concerning middle school agricultural motivation. Additionally, teachers will be able to use the findings of this study to alter teaching methods to in clude tactics which will enhance student motivation and engagement. Lastly, teachers and administrators will be closer to closing gaps in student achievement and meeting objectives mandated by the No Child Left Behind Act (2002).

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31 CHAPTER 2 REVIEW OF LIT ERATURE Chapter one explained the issue of low levels of student achievement and the high school dropout epidemic that have been facing the United States secondary school system for several decades. The literature focused on student motivation and engagem ent as points of intervention. Thus, the purpose of this study was to obtain middle school agricultural perspective on student motivation and engagement in learning. Chapter one also provided definitions, objectives, limitations, and as sumptions pertaining to this study. Chapter two provides the theoretical and conceptual frameworks that directed this study. In addition, this chapter offers substantial support for the study through findings of pragmatic literature. The literature review focused on defining agricultural education and explaining the foundations of student dropout indicators, stages of adolescent cognition, and student motivation and engagement in learning. Agricultural Education Agricultural Education has been described as the community of scholarship (Barrick, 1988, p.26). Agricultural education i n public schools has had an affluent history of developing personal skills of students and providing abilities needed for career employment through three main components: classroom and laboratory instruction, supervised agricultural experiences (SAE) and F FA (Huges & Barrick, 1993). Hughes and Barrick (1993) explained agricultural education through their program model (Figure

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32 2 1). The program model described agricultural education to take place within the context of school and community (Hughes & Barrick, 1993). Classroom and laboratory instruction uses instruction to teach technical agriculture, leadership, and personal development (Hughes & Barrick, 1993). SAE and FFA give educators a means to provide experiential learning opportunities, reinforce curric ulum taught in the classroom and laboratory setting, and provide motivation for students (Hughes & Barrick, 1993). It is important to note incentives such as contest s degrees, and awards outlined in the model (Figure 2 1) do not drive activities FFA and S but rather serve as reinforcement and motivation tools by recognizing students for exemplary performance (Huges & Barrick, 1993). While employment, education, and a career in agriculture are the intentions of the model, an agricultural e ducation program has been viewed as an asset in preparing students for productive lives in several careers ( Hughes & Barrick, 1993). Figure 2 1 Agricultural Education Program (Hughes & Barrick, 1993)

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33 Student Dropout ong been viewed as a serious educational and that has been facing the United States for more than three decades and has become something of a national obsession (Finn, 1989). Additionally, student dropout has been a continuing issue for many stakeholders within the educational system and has been noted as an issue which will continue for times to come (Rumberger, 1987). Accordingly, while the rates of high school dropouts have decreased from 60% in the 1940s to less than 16% in the 1980s (Rumberger, 1987) student dropout rates have not been de creasing at a rate to meet current goals of a 90% national graduation rate by 2020 ( Civic Enterprises Everyone Graduates Center, 2012 ). In fact, high school dropout rates, which are currently at 15%, have barel y decreased beyond those reported in the 1980s ( Civic Enterprises Everyone Graduates Center, 2012 ). Ultimately, student dropout has been noted to provide several individual and social concerns (Rumberger, 1987). Accordingl high school prior to completion has economic and social well Social Consequences of Dropout Drop ping out of school has been noted to affec t not only individual students but also society as a whole ( Civic Enterprises Everyone Graduates Center, 2012 ; Rumberger, 1987). Rumberger (1987) indicated seven social consequences of dropping out of school as: ( 1) f orgone national income; (2) f orgone tax revenues for the support of government services; (3) i ncreased demand for social services; (4)

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34 i ncreased crime; (5) r educed political participation; (6) r educed intergenerational mobility; and (7) p oorer levels o f health (p.114 115). The most cited social consequence of student dropout has been forgone income (Rumberger, 1987). The forgone income of the cohort of dropouts of the 1981 national high school class amounted to $228 billion, resulting in forgone governm ent revenues of more than $68 billion (Rumberger, 1987). Social consequences have continued to arise from dropping out of school. By completing high school the dropouts of the national grad u ation class of 2011 would have generated up to $154 billion addit ional earnings over their lifetimes ( Civic Enterprises Everyone Graduates Center, 2012) Additionally, graduating half of one class of dropouts would save the U.S. taxpayer $45 billion a year, as the average dropout cost s the economy $240,000 over his or h er lifetime in lower tax contributions and higher reliance on social services ( Civic Enterprises Everyone Graduates Center, 2012 ; National Center for Educational Statistics, 2009). Ultimately, dropout students will continue to place burdens on social welfa re programs (Finn, 1989). Individual Consequences of Dropout Dropouts have continued to suffer the struggle of obtaining steady, well paying will be more disadvantaged in the ever changing global job market than ever before (Rumberger, 1987). Students today and in the future will be required to not only complete high school but also seek further education ( Civic Enterprises Everyone Graduates Center, 2012). Dropout beha viors have been associated with poor academic performance in school, which has been measured through grades, test scores, and grade retention

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35 (Rumberger, 1987). Behavioral problems such as absenteeism and discipline problems have also been associated with dropping out of school (Rumberger, 1987). Finally, students who have the potential to become dropouts have lower levels of self esteem, a sense of less control over their lives poorer attitudes toward school, and lower educational and professional ambitio ns (Rumberger, 1987). Preventing Dropout (Rumberger, 1987, p.111), and has been noted to be triggered by early school failure (Finn, 1989). Additionally, academic failure has been noted to have a direct effect on student motivation, thus resulting in a lack of engagement and ultimately dropout behavior (Mac Iver & Mac Iver, 2009). Student motivation and engagement in learning have been noted as factors for intervention and prevention of student dropout (Fredricks et al., 2004; Lee & Smith, 1993, Jang, 2008; Marks, 2000; Rumberger, 1987; Skinner et al., 2008; Taylor & Parsons, 2011). Identifying potential dropouts a t an early age has been noted to be the most beneficial to providing effective interventions (Barrington & Hendricks, 1989; Lee & Smith, 1993; Jang, 2008; Rumberger, 1987). Barrington and Hendricks (1989) found that by middle elementary years characteristi cs of potential dropout are apparent. Mac Iver and Mac Iver (2009) suggested that low levels of attendance, course failure in English or mathematics, and a record of poor discipline have been evident in dropouts as early as the sixth grade and predict at l east 50% of eventual dropout. class, and display low efforts are all indicators of disengagement from school and

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36 strongly predict eventual dropout (Balfanz et al., 2007). Moreover, experiencing course (Balfanz et al., 2007). Balfanz et al. (2007) was convinced that the combination of becoming an adolescent and moving into new structures of schools that consist of complex academic and social demands creates conditions that can push students off the path of graduation. Balfanz et al. (2007) demanded that these conditions required attention and called for proactive and preventive interventions at the middle grade levels. Cognitive Development of Adolescents Ryan and Patrick (2001) indicated early adolescence as the most precarious stage has been noted to mark th e beginning of a downward movement in academics, as it is the stage in which children become uncertain in their abilities to succeed in school and theory of cognitive deve The first person to evolve a theory of child cognitive development was Jean Piaget (1 896 1987) (Fisher, 2005). Piaget believed that knowledge is built through interacting characteristic of constructivism (Salkind, 2008). According to Piaget, the goal of i ntelligence is to achieve cognitive equilibrium (a reasonable, congruent relation) between cognitive structures (thought processes) and the surrounding environment (Fisher, 2005).

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37 hich exhibit organi zation and adaptation, in which organization is defined as cognitive structures arranged into rational systems to promote adaptation to the environment (Fisher, 2005). Piage t defined adaptation as a comple mentary process between assimila tion and accommodation (Fisher, 2005), where assimilation gives the meaning of incorporating experiences into existing knowledge (Salkind, 2008) and accommodation allows for new experiences to be created or for previous experiences to be adjusted to aspect s of the accommodation and assimilation explain development as a constant process that results in the structural change of differentiation and integration of knowledge (Salkind, 2008). Piaget recognized development as a continuous process and developed stages children move through to develop cognition (Fisher, 2005). His goal was to denote the linear succession children encounter as they move towards a point of cognitive develop stages of intellectual development (Table 2 1) are designed to build on each other and develop in sequence (Salkind, 2008). Table 2 1 S tages of A dolescent C ognit ive D evelopment Stage Age Sensorimotor Intelli g ence Birth 1.5 2 Years Preoperational Intelligence 2 7 Years Concrete Operational Intelligence 7 11 Years Formal Operational Intelligence 11 Adulthood Note. Source: (Fisher, 2005; Salkind, 2008)

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38 Sens orimotor intelligence Piaget believed that infants are not capable of mental thought but only overt action schemes, such as basic reflexes like grasping or sucking (Fisher, 2005). He believed infants to be egocentric, in that their initial experiences of t he world are centered on their own bodies because they have not developed the ability to understand themselves as individual objects amongst other independent objects (Salkind, 2008). Piaget created six sub stages within the sensorimotor stage in which chi become more complex unified, and goal oriented (Fisher, 2005). Ultimately, this stage of development accumulates with the achievement of the concept of object permanence, in which adolescents understand that objects continue to exist independent of their own activities (Fisher, 2005;Salkind, 2008). Preoperational intelligence functioning (mental representation). In this stage, children are able to understand objects that are not in the immediate spatio temporal field (Fisher, 2005; Salkind, 2008). Ultimately, children develop the notion of preconceptual thought, which includes pretend play, drawing, recall memory, and language (Salkind, 2008). Concrete operat ional intelligence During the concrete operational intelligence stage children are able to overcome the logical deficiencies of the preoperational stage (Fisher, 2005; Salkind, 2008). they do not solely focus on their own bodies (Fisher, 2005).Ultimately, children are able to create thoughts which are bound by concrete and physical reality, and children are able to put objects together and place them into one to one correspondence (Fish er, 2005; Salkind, 2005).

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39 Formal operational intelligence Once children have reached the formal operational intelligence stage they have developed the ability to surpass operating on concrete objects and are able to operate on logical forms of thought (Sa lkind, 2008). Children in this stage are able to discriminate between thoughts of reality and actual real i ty (Fisher, 2005). Furthermore, adolescents develop hypothetical deductive reasoning, or the ability to explore general theories and all possible vari ables which influence outcomes, and are able to deduce or hypothesize outcomes (Fisher, 2005; Salkind, 2008). Ultimately, the formal operational Cognitive Development and Middle School Students Piaget believed that a child cannot understand instruction if he or she has not developed the structures of understanding (Salkind, 2008). Middle school has been defined as grades six, seven, and eight, and middle school childr en typically fall between the ages of eleven through thirteen. Furthermore, the middle grade years have been noted to be the most challenging for students emotionally and cognitively, as most l intelligence and formal operational intelligence (Fisher, 2005;Salkind, 2008). The Carnegie Council on Adolescent Development (1989) noted that serving schools which focus on middle school make a tremendou 13). Balfanz et al. (2007) indicated that current reform efforts have focused on making middle schools more academically exceptional by creating schools which are developmentally appropriate for students by adjusting for the developmental needs of an increased desire for autonomy, increased reflection on abstract concepts, and an increased need

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40 for positive and supportive relationships with peers and nonparental adults. Ryan and Patrick (2001) noted that changes in self reflection, autonomy, and identity exploration can lead to positive stude nt outcomes. Ultimately, Ryan and Patrick (2001) called for an intervention in the middle grade years in order to increase student achievement and promote graduation. Erik Erikson (1902 1994) was considered the father of psychosocial development and school psychology (Lee, 2005). He was concerned with the psychological development of children throughout their lifespan and focused on the importance of children move through eight stages in their life span and within each stage are faced Table 2 2 S tages of H uman D evelopment Stage Psychosocial Task Oral Sensory Trust vs. Distrust Muscular Anal Autonomy vs. Doubt Locomotor Genital Initiative vs. Gilt Latency Industry vs. Inferiority Puberty and Adolescence Identity vs. Role Confusion Young Adulthood Intimacy vs. Isolation Adulthood Generativity vs. Stagnation Maturity Identity vs. Despair Note. Source: (Lee, 2005)

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41 Oral sensory stage During this stage the psychosocial task children encounter is trust vs. distrust. According to Erikson (Lee, 2005), the task of trust vs. distrust reflects the significance of trustfulness displayed from caregivers. Muscular anal sta ge In this stage, children encounter the psychosocial task of autonomy vs. doubt. The control of their ability to regulate or control their own physical behaviors such as potty training (Lee, 2005). Eventually, the change of control will result in a successful feeling of control over his/her behavior for a child rather than feelings of less control (Lee, 2005). Locomotor genital stage Children encounter a psychosocial task of initiative vs. guilt in this stage of social expectations arise for children to have independent movement and motivation (Lee, epe ndency on parents towards the own ability to meet personal needs. In this stage, children are seen to become more capable of initiating more complex actions on their own, which results in more satisfaction than was possible when they depended on their p arents (Lee, 2005). Latency The psychosocial task seen in this stage involves industry vs. inferiority. This is crucial for children to master social skills which a re necessary to compete and function in society (Lee, 2005). Cultural experiences are seen to take precedence in this

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42 Children must be able to develop their own wor ld, and when faced with unsuccessful experiences children will develop a sense of inferiority and/or a lack of worthiness (Lee, 2005). Puberty and adolescence Children face the psychosocial task of identity vs. role confusion during this stage of Erikson of childhood and entrance into adulthood (Lee, 2005). In this stage children are expected to develop their identity and definition of self (Lee, 2005). Erikson indicated th at the development of their identity begins with defining an interest in career choices, furthering education, trade skills, and family (Lee, 2005). According to Fisher (2005), if adolescents face prolonged periods of identity confusion, especially in cul tures which encourage a high degree of choice, they will not be able to develop a sense of ego identity. Without a fully developed sense of ego identity adolescent s will not have sufficient ego strength of fidelity to function as an adult and will continu e to function with adolescent like regressive behaviors throughout their lifetime (Fisher, 2005). Young adulthood In young adulthood adolescents are faced with the psychosocial task of intimacy vs. isolation. In this stage adolescents encounter new tasks and create goals that directly involve other people. Individuals are expected to further develop and meet career goals (Lee, 2005). This stage marks a beginning into the developmental process of interacting with others of the same and opposite sex (Lee, 2 005).

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43 Adulthood In adulthood young adults face the psychosocial task of generatively vs. stagnation. Young adults are expected to define a style or life role in this stage and society places an emphasis on the continuity of proceeding with former stages ( Lee, 2005). According to Erikson, a sense of generatively comes from the need to support and encourage the development of the next generation (Lee, 2005). Conversely, individuals who can no t lend continuity to the next generation become absorbed in personal needs and begin to ignore others and become stagnated (Lee, 2005). Maturity adults age Erikson indicates that they begin to develo p ego integrity in which they come to realize that they have led meaningful and productive lives, and they begin to dispense their wisdom to young children (Lee, 2005). Motivation Motivation, in terms of academics, has been defined as what drives a student to partake in a given learning a ctivity (McLaughlin et al., 2005). According to McLaughlin et or her interest in the activity or the subject matter. Accordingly, students are known to be motivate d by several influences, including internal, external, positive (or interest), and negative (fear) influences (McLaughlin et al., 2005). Motivation theorists have argued that motivation involves the performance of all learned responses in which a learned b ehavior will not occur unless it is activated (McLaughlin et al., 2005). The earliest motivation theories were derived from a biological perspective, which stated that people are inherently determined to uphold an optimal level of excitement

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44 because it is physiologically pleasing (McLaughlin et al., 2005). However, the biological perspective has failed to address the workings of the mind. Therefore, a school of thought based on cognition evolved (McLaughlin et al., 2005). The beliefs of motivation based on cognition included the notions that individuals motivate behavior, and people change behavior to align with what they believe to be true (McLauglin et al., 2005). The social motivation theory stemmed from motivations of cognition, and social theorists hav e believed that students are motivated to mimic positive models and yearn to be accepted as part of a group (McLaughlin, 2005). Additionally, h umanistic theories of evaluation, and that people are motivated by inner feelings of worth, self esteem, self efficacy, and control (McLaughlin, 2005). Over the past 30 years researchers have focused on theories of motivation which ivational underpinnings of behavior (Wigfield & Wentzel, 2007). Numerous theories of motivation McLauglin et al. (2005) noted that academic motivation stemmed from a combination of cognitive, social, and humanistic theories of motivation, which included expectancy value theory, self determination theory, and achievement goal theory (Dolezal, 2011; McLaughlin, 2005; Wigfield & Wentzel, 2007). Expectancy Value Theory of Motivation Expectancy value theory has been noted to be coherent with major theories of motivation, has been used to observe motivation in classrooms, and has been linked to student achievement (McLauglin et al., 2005). The key theme of the expectancy value theory indicates that students do not engage in experiences unless there is a

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45 reasonable expectation of success and they find value in the activity (McLaughlin et al., 2005). This theory can be better understood by explaining the two components exp ectation and value. Expectation. Self efficacy is at the core of the expectation component of the expectancy value theory (McLaughlin et al., 2005). Self efficacy has been described as plement behaviors in particular situations (McLaughlin et al., 2005; Wigfield & Wentzel, 2007). According to his or her self perception of efficacy, which has been assoc iated with persistence and performance in school. Additionally, Wigfield and Wentzel (2007) stated that efficacious students take on more strenuous academic challenges, persist longer in struggles, and carry beliefs that they will succeed in school. Finall y, McLaughlin et al. (2005) noted between prior events and current self efficacy. Value. Value consists of what students value and how they decide what to value ( McLaughlin et al., 2005). Value refers to the motives and enticements students view for participating in learning tasks, which include interest in activity, importance of the activity to the individual, and the apparent worth of the activity (Wigfield & We ntzel, 2007). In addition, Wigfield and Wentzel (2007) argued that a student s ability to identify with teachers and peers aides him/her in determining the value of classroom activities. McLaughlin et al. (2005) noted that the value a learning activity hol ds for a student is what attracts the student into action. In these terms, value can be considered more than mere interest in a learning activity, but as the cause for a student wanting to complete

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46 the tasks (McLaughlin et al., 2005). Ultimately, value can arise from interest in the subject matter of learning activities, or from a sense of the effectiveness of undertaking tasks (McLaughlin et al., 2005). Self Determination Theory of Motivation Self determination theory suggested that learning can only occ ur when individuals become cognitively and emotionally engaged in learning tasks (Dolezal, 2011). According to the theory, every individual needs the comprehension of the fundamental needs of autonomy, competence, and relatedness (Dolezal, 2011). The need for s within he human need to control desired outcomes and feel successful in bringing the desired outcomes refers to an in need for competence (Dolezal, 2011). T he need to feel a sense of belonging to a social group Achievement Goal Theory of Motivation Achievement goal theorists have noted student behavior as a means to achieve special goals and that students aim to achieve academic performance and mastery goals. Dolezal (2011) described students who pursue mastery goals to be self regulating and self determining and believed that intelli gence will increase wi th effort. Students who have shown interest in performance and mastery goals are known to be concerned with their own abilities, how well they can perform, and how others perceive them (Dolezal, 2011). Motivational Behaviors over Time Factors which motiv ate an individual s behavior have been known to change throughout time (McLaughlin et al., 2005). Appropriately, factors which have been noted

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47 to motivate first grade students are not expected to motivate the same students once enrolled in high school (McL aughlin et al., 2005). However, some forms of extrinsic motivation (such as social acceptance) have been known to remain unchanged (McLa ughlin et al., 2005). Wigfield and Wentzel (2007) denoted that students who continue to hold beliefs of self control ove r learning and have autonomy over aspects of learning tend to become more engaged in their learning activities. Fundamentally, motivation has been noted to directly impact social and academic functioning of individuals (Wigfield & Wentzel, 2007). Engageme nt Learning has been noted to develop due to the effort of the student, who must be enticed to participate in an ongoing cycle of studying, producing, correcting mistakes, and starting over (Newmann et al., 1992). Engagement has become an important compone nt of motivational research, because it has been considered to be an outward manifestation of a motivated student (Skinner et al., 2008). Engagement emerged as the core theoretical framework to explain student dropout and has been noted as the most promisi ng method to preventing the phenomena (Appleton et al., 2006; Finn, 1989). Additionally, educators have recognized the importance of student engagement in learning and have noted that too many students appear to be bored, unmotivated, uninvolved, and disen gaged from the academic and social aspects of school (Appleton, Christenson, & Furlong, 2008). Moreover, research has indicated that students invest the majority of their energy in performing rituals, procedures, and routines, and fail to develop substanti al understanding (Newmann et al., 1992). Ac cording to Skinner, Kindermann and activities predicts achievement and completion in school.

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48 Engagement has been generally defined as active invo lvement, commitment, and concentrated attention in an activity (Newmann et al.,1992). In terms of academics, engagement has been defined as a psychological process in which students devote their undivided attention and efforts to an endeavor of schooling a ctivities, goals, and values in order to master knowledge and skills that academic work is intended to promote (Marks, 2000;Newmann et al., 1992; Skinner et al., 2009). Accordingly, engagement represents a potentially impressionable influence in shaping ad academic retention, achievement, and resilience (Skinner et al., 2009). In addition, engagement has been known to capture the quality of participation in classroom learning activities and create energized, focused, and positive interactions with academic activities rather than apathetic withdrawal (Skinner et al., 2009). Engagement has been noted to vary in force and duration. Students have been known to become engaged in short term, specific situational contexts or in a long term, stable contex t (Fredricks et al., 2011). Ultimately, rates of student engagement have been known to stem from opportunities for participation, interpersonal relations, and intellectual endeavors within the school or classroom (Fredricks et al., 2011). Historically, en gagement was measured using attendance, test scores, truancy, and graduation rates data and was viewed as a method of reclaiming at risk dropout students and managing classroom behavior (Taylor & Parsons, 2011). Using these types of data resulted in track ing student achievement levels but failed to gauge student engagement in learning (Taylor & Parsons, 2011). Current research describes engagement as a meta construct which incorporates multiple components of engagement (Fredricks et al., 2004; Newmann et al., 1992;

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49 Taylor & Parsons, 2011). Traditionally, the literature has indicated that engagement unifies the components of behavioral, emotional, and cognitive engagement (Appleton et al., 2006; Fredricks et al., 2004). Behavioral Engagement Behavioral en gagement describes the idea of participation in a learning task (Fredricks et al., 2004). Behavioral engagement includes involvement in academic, social, and extracurricular activities, and is considered vital to reaching positive academic outcomes and pre venting student dropout (Fredricks et al., 2004). Behavioral engagement has also been known to include positive conduct, effort, and participation (Appleton et al., 2006). Additionally, behavioral engagement can range from doing work and following the rule s to participating in organizations like student council (Fredricks et al., 2004). Ultimately, behavioral engagement has been noted to be measured by student conduct, persistence, and participation in learning tasks (Fredricks et al., 2004). Cognitive Eng agement Cognitive engagement implicates the idea of investment and has been noted to integrate the eagerness to exert the necessary effort to compare complex ideas and master difficult skills (Fredricks et al., 2004). Cognitive engagement has been noted to regulation, learning goals, and investments in learning (Appleton et al., 2006) and can range from memorization to the use of self regulated learning strategies, which promote understanding and expertise in a skill (Fredricks et al ., 2004). Ultimately, cognitive engagement has been conceptualized as psychological investments in learning and has been measured through problem solving, preferences for rigorous work, independent work styles, and methods of coping with perceived failure (Fredricks et al., 2004).

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50 Emotional Engagement positive attit ude toward learning, as well as a sense of belonging (Appleton et al., 2006). The construct of emotional engagement includes positive and negative reactions to teachers, peers, academics, and the school environment and has been presumed to Additionally, emotional engagement can range from a straightforward liking of school to emotional engagement has been measured through self reported measures of positive and negative emotions towards school, school work, and people at school (Fredricks et al., 2004). How do Learners Become Engaged? Taylor and Parsons (2011) raised the question of determining how students are engaged. Literature indicated that eng agement can be a form of a meta construct which combine s forms of engagement, including academic, cognitive, intellectual, institutional, emotional, behavioral, social, and psychological engagement (Taylor & Parsons, 2011). Taylor and Parsons (2011) questioned whether a student must be engaged in all types of engagement to be considered successful. Accordingly, Dunlevy, Milton, and Crawford (2012) found in their research that: Students want to experience work that is meaningful and not easy: They want to work with ideas that matter, solve real problems, learn from each other, people in their communities, and experts, and want to engage in dialogue in their classes (p.1).

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51 Ultimately, Taylor and Parsons (2011) indicated four major ways for educators to engage students in learning tasks, including focusing on are as of interaction, exploration, relevancy, and multimedia and instruction. Interaction Considerate relationships and interactions have been shown to improve student engagement (Taylor & Parsons, 2011). In their study, Willms, Friesen, and Milton (2009) fou nd that students stated a need to interact with people within and beyond the environment of the classroom and school. Students indicated that they desire environments which promote supportive connections and provide continuous interactions (T aylor & Parson s, 2011). Taylor and Parsons (2011) argued that students must have social interaction to be fully engaged in academic tasks. Exploration Ta ylor and Parsons (2011) found that learners seek opportunities to explore and find solutions for themselves. Additi onally, Hay (2000) found that students yearn for more hands on experiences and are less willing to absorb information that is placed in front o f them. Lastly, Taylor and Parsons (2011) argued that students value seeing how ore engaging than learning about it in class. Relevancy Taylor and Parsons (2011) found that students want their learning to be applicable to their lives as opposed to being theoretical and text based. Providing students the ability to work with genuine problems or community based issues promotes student engagement and builds a purpose in the learning (Willms et al., 2009 ; Taylor & Parsons, 2011) Ultimately, research findings have shown that students need to feel as if academic work is worth their time (J ang, 2008; Willms et al., 2009).

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52 Multimedia and Instruction Duleavy and Milton (2009) found multimedia and technology (like cameras, videos, Smartboards, gaming software, PowerPoint) to be helpful in engaging students in learning about subjects and help students control their own learning. Additionally, Taylor and Parsons (2011) found that students desire to interact globally with people and events, and that by using multimedia and technology educators are able to provide learners with accessible and pert inent information and experts. Conclusively, teachers have reported that the use of technology and multimedia have proven to increase the factors of student cognitive, affective, behavioral, academic, and social engagement (Taylor & Parsons, 2011). Motiva tion and Engagement To date motivation research has been considered to be fragmented, and a call for a more comprehensive approach to research has been seen in this area (Martin, 2007; 2008; 2009). Additionally, a number of educational and psychological t heories have been identified to describe the nature of human cognition and behavior (Martin, 2007; 2008; 2009). Martin identified three significant levels of commonalities which provided direction in the creation of the fundamental dimensions of motivation and engagement. Martin (2007; 2008; 2009) stated that: Level one delineates cognitive and behavioral components of work entailing cognitive and behavioral orientations to learning strategies; cognitive antecedents of behavioral strategies in environment al demands; cognitive behavioral approaches to engagement and behavioral changes, and cognitive affective and behavioral dimensions of academic engagement. Level two demonstrates differential empirical strengths of components of motivation and engagement for example, self efficacy reflects highly handicapping behaviors reflect maladaptive engagement.

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53 Lastly, level three informs the structure of motivation and engagement frameworks, es pecially those which demonstrate the hierarchical models of human cognition and behavior (p.797, 2009 ). Martin (2008) ultimately defined motivation and engagement as students force and drive to engage, learn, work effectively, and achieve potential at sc hool. He noted that engagement and motivation underpin student achievement and play large roles in Through his research Martin (2008) identified motivation and engagement as a multidimensional construct and d eveloped the Motivation and Engagement Wheel (Figure 2 2). Figure 2 2 The Motivation and Engagement Wheel (Martin, 2008; 2009)

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54 The Motivation and Engagement Wheel The Motivation and Engagement Wheel (MEW) describes an integrative framework that refle cts seminal motivation and engagement theories (Martin, 2007; 2008; 2009). Martin (2007; 2008; 2009) developed the MEW for practitioners who sought to capture the diversity of motivation and engagement dimensions. Martin (2007; 20 0 8; 2009) was driven to cr eate the MEW by the need of practitioners to have a 2009) purpose in creating the MEW was to bridge the disparities between the dimensions of educational theories and pr actitioners, and create a framework which would be readily accessible for practitioners, parents, and students. The MEW is designed with separated components which reflect adaptive and maladaptive dimensions. These dimensions aim to assist practitioners a nd students in (2007) indicated that when students are able to understand the dimensions of motivation and engagement, an intervention is more likely to be successful, as i t is more meaningful to the student. In the MEW, Martin (2007; 2008; 2009) characterized motivation and engagement into four higher order groups, including adaptive cognitive dimensions, adaptive behavioral dimensions, impeding/maladaptive cognitive dimens ions, and maladaptive behavioral dimensions. Martin (2007; 2008; 2009) stated that the higher order conceptualization addresses the aims of enhancing carefulness, provides amalgamating approaches to seminal educational and psychological theories, and offer s an opportunity to comprehend basic structures of student motivation and engagement. Furthermore, a basis for measuring student motivation and engagement must exist, thus, a lower level of constructs which reflect diversity of student academic

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55 engagement and motivation are guided through theory and research to operationalize lower order constructs were identified through seven substantive questions for the development of mot ivational science proposed by Pintrich (2003) from salient and seminal theories which included: self efficacy, attributions, control, valuing, goal orientation, self determination, need achievement, self worth, and self regulation. Self Efficacy and Expec tancy Value Theory Students who exhibit high self efficacy are inclined to create and question alternative sources of action when they are not initially met with success (Martin, 2007). Individuals who have high self efficacy have been noted to perform be tter in classrooms due to their elevated levels of effort and persistence (Martin, 2007). Finally, students who have high self efficacy tend to handle problem situations more efficiently by using cognitive and emotional processes related to the situation ( Martin, 2007). Martin (2007) indicated self belief as a critical component to student motivation. He also noted that the interaction of experiences and task value predicts student motivation and engagement (Martin, 2007). Additionally, individuals who hav e high expectations and value tasks are more motivated and engaged to complete those tasks (Martin, 2007). Fundamentally, self efficacy and value of school is reflected in the self efficacy and value dimens ions of the MEW model (Figure 2 2) (Martin, 2007; 2009). Attribution Theory and Control Attribution theory explains the reasons an individual accredits to an experience may determine how the individual behaves in future occurrences (Martin, 2007). Martin (2007) noted that attributions created in the cla performance. Accordingly, Martin (2007) stated that attributions of outcomes can vary

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56 to setbacks, pressure, and fear of failure. Conclusively, from an attribution theory perspective Martin (2007; 2009) indicated control as an important construct to include in the MEW, and attributions and control are reflected in the dimension of uncertain control (Figure 2 2). Goal orientation an d self regulation Goal orientation indicates an (mastery orientation) and performance on the task (performance orientation) (Martin, 2007). Mastery orientation is driven by intrinsic motivation and is more d irectly pertinent to the framework of motivation and engagement than performance orientation, which is driven by extrinsic motivation (Martin, 2007). Martin (2007) noted that mastery orientation is a critical element of student motivation and that it is ma nifested in the lives of students through self regulatory behaviors, such as planning, study management, and persistence. In addition, self regulation and motivation have been found to be predictive of student achievement and adaptive orientations of acade mic tasks (Martin, 2007). Self determination and motivation orientation are present in the mastery orientation dimensions, and self regulation is reflected in the planning, task management, and persistence dimensions of the MEW (Figure 2 2) (Martin, 2009). Need achievement and self worth motivation theory According to the need achievement and self worth models of motivation, students can be categorized as success oriented, failure avoidant, and failure accepting (Martin, 2007). 1. Success oriented students: The success oriented student is noted to be optimistic, proactive, and positive towards his or her studies, and is not

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57 debilitated by setback but rather is able to respond with optimism and energy (Martin, 2007). 2. Failure avoidant students: The failure av oidant student is noted to be anxious, motivated by his or her fear of failure, and may even handicap his or her chances of success in order to create an excuse for not performing well (Martin, 2007). 3. Failure accepting students: The failure accepting stud ent has given up to the extent of not trying to avoid failure, is often disengaged from his or her studies, and has learned to display helpless patterns of motivation (Martin, 2007). Success oriented students show signs of higher self efficacy and control and failure avoidant and failure accepting students show signs of anxiety, failure avoidance, self handicapping, and disengagement (Martin, 2007). Self worth and need achievement are reflected in the failure avoidance, anxiety, self handicapping, and dis engagement dimensions of the MEW (Figure 2 2) (Martin, 2009). Empirical Research Dolezel Dolezel (2011) conducted a study on student and teacher perceptions of motivation and engagement. The study utilized 144 students in grades 6 12 focusing on gender, grade, and the qualification for free or reduced lunch, as well as, 36 teachers who taught in grades 6 12 of whom none where in their first 3 years of teaching. Dolezel (2011) administered a 42 item Likert type instrument with one open ended question foc using on three subscales including instructional strategies, teacher relationships/expectations, and goals/motivation theory. Students were instructed to think about a particular class in which they felt motivated and engaged in while responding to the ins trument. Instructional strategies. Students reported classes in which students were allowed to work collaboratively and engage in projects that had real life applications

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58 were most motivating and engaging (Dolezel 2011). Dolezel (2011) found data to be supported by Yazze engaged and motivated with methods that involved working and learning with peers. Conversely, students reported that having the ability to choose their own topics of study as a n instructional strategy was not being used as often by teachers in classes students considered motivation and engaging (Dolezel, 2011). Teacher relationships/expectations. Dolezel (2011) findings were consistent ents who do not feel supported and respected by teachers are more likely to lack engagement and motivation. Students reported that they are more motivated and engaged when their teachers like them, want them to do well, and are fair thus implying that pos itive relationships with teachers are an important component of a classroom which students find to be motivation and engaging (Dolezel, 2011). Dolezel (2011) noted that teachers should be aware that all behaviors are noticed by students and can be interpre ted as caring, showing indifference, or even dislike for a student. Goals/motivation theory. Students identified effort and learning strategies as attributions which lead to academic success (Dolezel, 2011). Additionally, students signify receiving good g rades in school motivated them to be engaged, as they were eligible for extracurricular activities, college acceptance, pleasing parents, and meeting motivated by rewards othe r than those which are immediate and extrinsic and found th ese to be consistent with Ryan and determination theory.

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59 Ultimately, Dolezel (2011) noted positive relationships with teachers appeared to be the most power indicator for studen t motivation and engagement. Additionally, students desire classroom environments in which teachers hold high expectations for learning and use instructional strategies that allow learning to be adapted to real life applications (Dolezel, 2011). Turner and Herren Turner and study of 15,000 high school agricultural education students found students to have the highest need for achievement and th e lowest need for power Overall, all agricultural education students expressed a higher need for a chievement than affiliation over power and a higher need for affiliation than power (Turner & Herren, 1997). When compared to non members agricultural education students who were members of FFA had a high er need for achievement a high er need for affiliati on and a higher need for power (Turner & Herren, 1997). No statistically significant differences were found based on gender for the need for achievement (Turner & Herren, 1997). Female students were found to have a highe r need for affiliation and a higher need for power than male students enrolled in agricultural education classes (Turner & Herren, 1997). As a result of their findings Turner and Herren (1997) suggested agricultural educators should emphasize activities that appeal to agricultural education need for affiliation. Female agricultural education students need activities which will meet their need for affiliation and need for power more than male agricultural students (Turner & Herren, 1 997).

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60 Rohs and Anderson Rohs and Anderson (2001) noted few studies to focus on the perspectives of students on their motivational needs and no studies to focus on middle schoo l students. According to Rohs and Anderson (2001) middle school students need mo re hands on activities and teamwork tasks and school based agricultural education has been tailored to meet these needs of the developmental stages of a dolescents. Additionally, Rohs and Anderson (2001) noted that by exploring the motivation needs of stud ents classes. Rohs and Anderson (2001) conducted a study using 14,115 seventh and eighth grade students in 38 school based agricultural education programs in Georgia f ocusing on FFA and non school students were found to have the highest need for achievement (M=3.97), with a second need for affiliation (M=3.63), and lastly a need for power (M=3.33) (Rohs & Anderson, 2001). No significant difference between FFA and non FFA students was found (Rohs & Anderson, 2001). Females were found to be more concerned with relatio nships and influence than males; however, there was no significant difference found for ach ievement between males and females (Rohs & Anderson, 2001). Ultimately, Rohs and Anderson (2001) noted that the developmental stage of adolescence is a period of self discovery, and exploratory teaching methods can le a d to helping student develop motivati onal needs. Additionally, teaching methods should be developed to meet the current motivational needs of students and can be used to aide students in self discovery for continual personal development (Rohs & Anderson, 2001). Finally, activities which are d esigned to experiment with personal developmental

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61 characteristics can assist in developing motivational needs that become more evident as students mature (Rohs & Anderson, 2001). Martin Martin (2008) implemented workshops within youth enrichment programs which targeted student engagement and motivation. The purpose of the study was to create (Martin, 2008). Martin (2008) implemented an intervention of self complete modules ove r a school term using 53 high school boys in a capital city of Australia. Using the Motivation and Engagement Scale High School (MES HS), Martin (2008) administered a pre intervention and post intervention assessment for the treatment and control group. D ata collected showed gains on key factors of student motivation at the end of the workshop sustained six to eight weeks later (Martin, 2008). Moreover, the treatment group demonstrated positive motivation changes on task management, persistence, anxiety, f ailure avoidance, and uncertain control (Martin, 2008). Furthermore, compared to a comparison group, the treatment group exhibited positive shifts on valuing, mastery orientation, planning, task management, persistence, failure avoidance, uncertain control and self handicapping (Martin, 2008). Ultimately, the cumulative results of the study findings demonstrated the potential for multidimensional interventions for enhancing student motivation and engagement. Upon completion of the 2008 study Martin noted that students across all grade levels share commonalities (2009). Martin (2009) argued that Students must apply themselves over a sustained period of time to develop academic skills, engage with key performance demands, negotiate the rigors of competitions deal with setbacks and adversity, cope with possible self doubt and uncertainty, and develop psychological and behavioral skills

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62 to manage the highs and lows of ordinary course work of their academic life (p.794 795). Martin (2009) felt it was practical to propose core and common constructs which were relevant and meaningful across academic life. He developed a study to investigate the developmental construct validity of the MEW (using the MES) across elementary, high school, and universities (Martin, 20 09). In his study, Martin (2009) distributed the MES to 624 upper elementary age students (9 11.5 years old) from five Australian schools, 21,579 high school students from 58 Australian schools, and 420 undergraduate students from two Australian universiti es. Martin (2009) found results which supported the developmental construct validity of motivation and engagement at the varying levels of the academic life span and found largely analogous findings among the very distinct educational stages. Data confirme d the generality of the MEW and the MES amongst young students through mature age students (Martin, 2009). Conceptual Model of Engagement and Motivation Martin (2007, 2008, 2009) provided instrumental research in evaluating student engagement and motivat The conceptual model (Figure 2 3), which served as a foundation for this study, was and Engagement Wheel (Figure 2 2). Findings from the literature review were also incorporated into the conceptual model (Figure 2 3) to account for factors which impact student motivation and engagement including: Nature of instruction Relationships Parental attitudes and expectations towards learning Peers Classro om climate

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63 School structure and culture Gender Age Grade level (Marks, 2000; Martin, 2008). Engagement Wheel. The MEW includes adaptive and maladaptive cognitions and b ehaviors that predict student engagement and motivation. External variables are found at the top of the model as they have been recorded to influence student engagement and motivation. These variables are broken into student and environmental attributes an d will be explained in further detail in the following sections. Student Attributes Student attributes was noted as the first component of external variables to influence student engagement and motivation. Attributes included gender, age, and grade level (Marks, 2000; Martin, 2007, 2008, 2009). Gender Marks (2000) found across all grade levels girls have been noted to be consistently more engaged in academics than boys. Additionally, Martin (2007) indicated that the number of high achieving Australian girls surpasses the number of high achieving boys, and that more females have been noted to complete school since 1976. Boys have also been noted to be more negative about school, have higher rates of discipline issues, view homework as less useful, are le ss likely to ask for help, and are more unwilling to complete extra school work (Martin, 2007). Finally, educators have noted that boys are ultimately less productive because they are less able to concentrate and less motivated to solve complex problems (M artin, 2007).

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64 Age Middle and high school students who are more academically successful have been noted to have greater engagement with school and class work. Martin (2007) self perception of competence and subjective value decline as children grow older. Grade level Marks (2000) discovered that engagement in academic work decreases as grade level increases. Martin (2007) noted that motivation and engagement decline in middle school years. As students transition into middle school cha nges in domain specific subjective task values become more noticeable (Martin, 2007). Ultimately, Martin (2009) found that upper elementary students (ages 9 11.5) reflect higher levels of motivation, which is consistent with previous research indicating de clines between elementary and middle or high school (Jang, 2008). Environmental Attributes The second component of external variables noted to influence student engagement and motivation was labeled as environmental attributes and included peer pressures societal norms, home influences, and institutional influences (Barrington & Hendricks, 1989; Dunleavy & Milton, 2009; Fredricks et al., 2004; Marks, 2000; Ryan & Patricks, 2001; Taylor & Parsons, 2011). Home influences Home influences have been noted t o affect student engagement and motivation (Barrington & Hendricks, 1989; Marks, 2000). In the conceptual model of this study home influences included cultural norms, parental attitudes and expectations, and parental/sibling relationships. Barrington and H endricks (1989) found results which

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65 suggested that parental attitudes should be more supportive in order to encourage motivation and engagement. Likewise, Marks (2000) found in his study that parental involvement supported engagement at all grade levels. Institutional influences Institutional influences have been proven to have a large impact on student engagement and motivation (Barrington & Hendricks, 1989; Dunleavy & Milton, 2009; Fredricks et al., 2004; Mac Iver & Mac Iver, 2009; Marks, 2000; Ryan & P atrick, 2001; Taylor & Parsons, 2011). In the conceptual model of this study institutional influences included the school structure and culture, the classroom learning environment, and nature of instruction. School structure and culture : In this study, sc hool structure and culture included teacher/teacher and teacher/administration relationships. Marks (2000) found that a positive school environment that supports student learning benefits student engagement. According to Mac Iver and Mac Iver (2009), schoo ls which promote personal relationships among teachers and students have shown improved student engagement. Furthermore, student course performance is related to how well teachers work together within the school (Mac Iver & Mac Iver, 2009). Student perform ance has also been noted to be higher in schools which promote high goals, positive work ethics, Classroom learning environment: In this study, the classroom learning environment included element s of teacher/student relationships and learning expectations. Marks (2000) found that the role of classroom support increases as progress through school. In Barrington and found that middle school students require pe rsonal attention from teachers and group

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66 counseling sessions to help meet their social needs, help them recognize their abilities, and to help them identify their options for future academic or vocational options. In addition, teacher support has been note d to influence behavioral, emotional, and cognitive engagement (Fredricks et al., 2004). Mac Iver and Mac Iver (2009) indicated student performance was related to relationships with teachers, especially where students can trust their teachers and teachers provide personal support to students. Additionally, open, caring, and respectful relationships between students and teachers have been noted to be necessary to develop social and psychological engagement (Taylor & Parsons, 2011). Taylor and Parsons (2011) found students desire stronger relationships with teachers, each other, and their communities. Students also want their teachers to know how they learn and to establish learning environments which build interdependent relationships and promote a culture of learning (Taylor & Parsons, 2011). Furthermore, Taylor and Parsons (2011) indicated that educators need to change how they teach and what they teach in order to engage learners. Conclusively, teachers who make expectations clear and provide steady respons es have students with higher behavioral engagement (Fredricks et al., 2004). When middle school students believe their teacher to be supportive, their value for communicating and interacting with the teacher is increased, they engage in more self regulated learning, and they are less likely to take part in disruptive behavior (Ryan & Patrick, 2001; Patrick et al., 2007).Ultimately, Patrick et al., (2007) found students who are provided with adaptive classroom enviro nments tend to focus on mastery and feelin gs of efficacy, and show engagement.

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67 Nature of instruction : In this study, nature of instruction included curriculum, teacher instruction ability, and subject interest. Marks (2000) found class subject matter proved to be a significant factor of engagemen t. Barrington and level of academic achievement is needed. Mac Iver and Mac Iver (2009) stated schools which provide less curriculum differenti ation among students have seen improvements in student engagement. Additionally, Mac Iver and Mac Iver (2009) indicated that their future. Taylor and Parsons (2011) f ound students want instruction which is intellectually engaging and relevant to their lives. Students also desire instruction to be presented in socially, emotionally, and intellectually engaging ways (Taylor & Parsons, 2011). Furthermore, Taylor and Parso ns (2011) indicated that effective teaching is distinguished by creating learning tasks which incorporate deep thinking, a student immersion in disciplinary inquiry, connections to the world outside the classroom, and substantive conversation (Willms, Frie sen, & Milton, 2099, p.34). Student Development The end result of the conceptual model is student development, which leads to either student achievement or student dropout if influenced positively or negatively through the conjunction of external variables motivational thoughts and behaviors (Barrington & Hendricks, 1989; Dunleavy & Milton, 2009; Finn, 1989; Fredricks et al., 2004; Marks, 2000; Martin, 2007; 2008; 2009; Patrick et al., 2007; Ryan & Patrick 2001; Taylor & Parsons, 2011).

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68 F igure 2 3 A Co nceptual Model for Motivation and Engagement (Adapted from Martin (20 07, 2008, 2009))

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69 Chapter Summary Chapter two introduced the theories which provided a foundational basis for this study as student dropout, adolescent cognition theories, theories of mot ivation, theories of engagement, and motivation and engagement theory. A conceptual model of motivation and engagement was presented based on these theories. Additionally, chapter two provided empirical literature to reinforce the conceptual model of motiv ation and engagement. The literature review suggested that theories of motivation and engagement are vast and broad, and most consider them to be disjointed. Martin (2007; 2008; 2009) developed the Engagement and Motivation Wheel as a means to connect inf luential literature and methods for practitioners. The MEW was viewed as a multi dimensional construct which combined theories of motivation and engagement in four higher order factors, including adaptive cognitions, adaptive behaviors, maladaptive cogniti ons, and maladaptive behaviors (Martin, 2007; 2008; 2009). The higher order factors of the MEW are operationalized through eleven lower order components, including self efficacy, mastery orientation, valuing, persistence, planning, task management, anxiety failure avoidance, uncertain control, self handicapping, and disengagement (Martin, 2007; 2008; 2009). External variables including student attributes (gender age, and grade level) and environmental attributes ( peer pressures, societal norms, home infl uences, and institutional influences ) were noted in the literature to impact student motivation and engagement and were incorporated into the conceptual model of this study. The conceptual model noted that external variables, in addition to positive and ne gative components of the MEW can result in either student achievement or dropout.

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70 CHAPTER 3 METHODOLOGY Chapter one of this study discussed the concerns of low student achievement and high school dropout which have been facing the United States secondary school system. The concepts of student engagement and motivation in learning were portrayed as possible interventions to increase student achievement and decrease the number of students dropping out of school. Additionally, definitions of significant term s, purpose, limitations, assumptions, and objectives of the study were presented in chapter one. Chapter two offered theoretical frameworks of student dropout, engagement, and motivation. Additionally, the conceptual model of student motivation and engage ment was described with supporting empirical literature. Chapter three describes the methodology of the study including research design, population, instrumentation, data collection and data analysis procedures. The purpose of this study was to ascertain the perspectives of middle school students on engagement and motivation in learning. Specific objectives of the study included: 1) reported perceptions of motivation to learn, 2) Identify middle sch reported perceptions of engagement in learning, 3) Examine the relationships between middle school agricultural education demographic characteristics ( age gender and grade level), and their perceptions of motivation to learn and engagement in learning. Research Design This study utilized a quantitative research perspective, as the purpose of quantitative research is to study cause and effects and relationships of a phenomenon (Ary, Jacobs, & Sorenson, 20 10). According to Ary et al. (2010), quantitative research

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71 can be conducted in the forms of experimental and non experimental research. This study was a form of non experimental research which utilized a descriptive/correlational research design. The rese archer considered a descriptive/correlational design appropriate to fulfill the research objectives. Descriptive research was utilized to address objectives one and two of this study because descriptive research provides the opportunity to gather informati on from groups of individuals, and provides the researcher the ability to opinions toward an issue (Ary et al., 2010). Additionally, correlational research was utilized to address objective three of this study because it enabled the researcher to gather data from individuals on gender, age, and grade level (independent variable s ) self perceptions of engagement and motivation in learning (dependent variable) (Ary et al., 2010). Validity of the Research Design According to Ary et al. (2010), researchers must be able to determine if the conclusions drawn concerning the relationships between the variables in the study are valid. Va internal validity, external validity, construct validity, and statistical conclusion validity. Int ernal Validity Internal validity has been noted as the basic requirement to interpret correct conclusions from a study (Ary et al., 2010). Ary et al. (2010) described internal validity as the observed changes in the dependent variable being caused by the independent variable(s) rather than by extraneous factors. Additionally, Ary et al. (2010) noted that

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72 the research design must control extraneous variables in order to eliminate alternative explanations of the outcomes. Several of the noted threats of vali dity described by Ary et al. (2010) were not considered to affect this study as they pertained solely to experimental designs. However, the four following types of threats were considered to apply to this study: selection bias, attrition, experimenter bias and subject effects. Selection bias : Selection bias has been noted to occur when the researcher must use intact groups and/or volunteers (Ary et al., 2010). For this study, middle school agricultural education instructors were invited to participate, an d those instructors who agreed to participate administered the MES to the students within their classrooms. Thus, selection of participants served as a minor limitation of this study. Attrition : The threat of attrition occurs when there is a loss of partic ipations from comparison groups (Ary et al., 2010). Attrition and/or nonresponse were considered threats to this study because data were limited to those students who chose to participate, were given permission by their parents, and were present the day th e MES was administered. Experimenter bias : Ary et al. (2010) indicated that experimenter bias occurs when the researcher has unintentional effects on the study. Experimenter bias was considered to be a limitation of the study as students were administered the MES JS by their teacher, which may have affected how students responded to questions on the instrument. However, to try to prevent experimenter bias, uniform protocols were developed and used in this study. Instructions were provided to teachers to be read verbatim to participants, and teachers were instructed to solely answer questions

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73 regarding the instructions and IRB consent. Finally, participants were instructed to place the instrument in a large envelope in order to ensure privacy and security. Subject effects : Subject effects were considered to be a minor limitation to this study. The MES perception of motivation and engagement in learning. Consequently, there was a possibility of students providing soci ally desirable answers. However, the researcher assumed that all participants answered in a truthful manner. External Validity According to Ary et al. (2010), external validity refers to the degree to which the conclusions of the study can be generalized to other subjects and settings. This study utilized a convenience sample Thus, the results of this study cannot be generalized beyond students similar to those used in this study. Construct Validity Ary et al. (2010) defined construct validity as the e xtent to which an instrument measures the psychological construct it is intended to measure. McMillan and Schumacher (2010) indicated three important construct validity threats to educational research. However, the researcher deemed only the two following threats as applicable to the research design of this study. Inadequate preoperational explication of constructs : To prevent the threat of inadequate preoperational explication of constructs, this study used well known constructs within educational researc h. Additionally, each construct was operationally defined according to the literature and the instrument used.

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74 Mono method bias : Mono method bias was recognized as a limitation of this study as the researcher utilized a self reported method as the sole m eans of data collection. Statistical Conclusion Validity Ary et al. (2010) defined statistical conclusion validity as the proper use of statistics to conclude that an observed relationship between the independent and dependent variable in a study is an a ccurate case of a cause and effect relationship rather than due to chance. Shadish et al. (2002) indicated several threats to statistical conclusion validity. However, most of these threats were deemed as not applicable to this study as they addressed expe rimental designs. The following threats were considered as applicable to this study. Low statistical power : To account for the threat of low statistical power the researcher used a uniform protocol for administering the instrument to help ensure condition s were the same when data were collected. Additionally, a reliable instrument was used in order to reduce measurement error (McMillan & Schumacher 2010). Violated assumptions of statistical tests : The assumptions of the statistical tests utilized in this s tudy were explained in the data analysis section in order to avoid violating assumptions of statistical tests. Unreliability of measures : Reliability estimates of the instrument were reported in the instrumentation section and were found to be satisfactor y by the researcher. Population The population of interest for this study included middle school agricultural education students in Florida. A convenience sample was used in this study based on geographical location to the researcher. An invitation to pa rticipate in this study (See

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75 Appendix A) was sent to twelve middle school agricultural educators in North Florida, and six educators agreed to participate in the study. The six educators who agreed to participate were located in Alachua, Baker, Clay, Gilch rist, Levy and Suwannee counties. T he students within the six classrooms of those agricultural education educators who agreed to participate became the accepting population of this study. Based on enrollment figures an estimated 700 instruments were sent t o participants among the six educators who agreed to participate in the study. A total of 218 instruments were received fro m participants; however only 213 were included in the analysis of this study as five instruments were incomplete. Instrumentation T his study utilized a directly administered questionnaire in order to increase the probability of receiving a high response rate (Ary et al., 2010). The Motivation and Engagement Scale High School was first developed by Martin (2007). In previous studies Ma rtin (2007) found the confirmatory factor analysis (CFA) to fit the data. Martin (2007) found the mean correlation between adaptive factors to be r = .33, the mean correlation between impeding factors to be r = .51, and the mean correlation between maladap tive dimensions to be r = .58, indicating that there was concurrent validity but sufficient distinctiveness to be retained as separate first order factors. Additionally, Martin (2007) found lower levels of shared variance between factor groups than within factor groups, which was indicated by a mean correlation between adaptive and impeding dimensions of r = 02, a mean correlation between adaptive an maladaptive dimensions of r = .41, and a mean correlation between impeding and maladaptive dimensions of r = .33.

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76 In a further study, Martin (2009) described the development of the Motivational and Engagement Scale across the academic life span, including junior high school, high school, and university. A pilot study conducted by Martin showed younger student s had difficulty differentiating the finer grained points on the 7 point scale. Martin (2009) indicated that in order to simplify the instrument for younger students, the scale was shortened to a 5 point Likert type scale versus a more typical 7 point scal e used in most studies Martin (2009) indicated that all three sample loadings were acceptable and was supported by acceptable reliability coefficients. Ultimately, Martin (2009) found invariance across junior high school, high school, and university setti ngs. The M otivation and Engagement Scale Junior School (MES JS) (See Appendix B ) was used in this study. The MES JS was designed to measure junior high school 13 years old) perception of motivation and engagement in learning ( Martin 2012). T he MES JS collected data on student motivation and engagement through three adaptive cognitive dimensions, three adaptive engagement dimensions, three maladaptive cognitive dimensions, and two maladaptive engagement dimensions (Life Martin 2012). The inst rument was a 44 item questionnaire comprised of four items for each of the eleven factors ( Martin 2012). The questionnaire was a 5 point Likert type scale with answer choices consisting of 1 ( Strongly Disagree ) to 5 ( Strongly Agree ) ( Martin 2012). Marti n (2012) reported psychometric properties based on data collected from 1,249 students across 63 classes in 15 junior high schools. A satisfactory fit to the data was reported from a first order CFA using LISREL 8.80 yielding ( x 2 =2,724.92, df=847) and a hig her order CFA ( x 2 = 3,197.18, df=886,) ( Martin 2012). A mean reliability

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77 ) for the eleven subscales was reported as .78 ( Martin 2012). The current researcher calculated a post hoc reliability analysis, the results of which will be reported in chapter four. Data Collection This study was approved by the Institutional Review B oard (IRB) at the University of Florida (See Appendix D ). After receiving IRB approval, data were c ollected between December 2012 and January 2013 Middle school agricultural educators were invited to participate in this study. After agreement to participa te in the study, packets containing administration protocols (See Appendix C), IR B consent forms (See Appendices E and F ), the MES JS (See Appendix B ), and a large envelope to collect the instruments were distributed to teachers. Teachers were instructed to read the script of IRB directions (See Appendix C) and distribute IRB consent forms to be sent home with students in order to obtain parental consent, as participants were minors. Once returned, IRB consent forms were collected and educators were instru cted to administer the MES JS to only those students who returned IRB consent forms. Additionally, teachers were provided a script of instructions (See Appendix C) to read aloud in order ensure consistency, and directions were also printed at the top of th e instrument. Upon completion of the instrument students were instructed to place their questionnaire in a large envelope in order to ensure privacy and security. Data Analysis Data were entered into Microsoft Excel by the researcher and analyzed using SP SS version 17.0 for Windows XP software. Research objectives one and two utilized descriptive statistics and included means, range frequencies, and standard deviations.

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78 Research objective three investigated relationships and correlations were utilized to analyze the data. Research Objective One Research objective one was to identify middle school agricultural education reported perceptions of motivation to learn. Data were collected using the MES JS to accomplish this objective. Instrument scoring procedures given by Martin (2012) in the MES JS test user manual were used to score the instrument. Scores for each question were entered into Microsoft E xcel to formulate raw scores for each construct. Raw scores were calculated using a formula p r ovided by Martin (2012), such as the following example. Self Belief : ((Q13 + Q 23 + Q33 + Q40 ) / 20) X 100) The following is an explanation of the formula: Q13, Q23, Q33, Q40 represent the four questions from the instrument which pertain to the self be lief construct which were added together. T he sum was then divided by 20 and multiplied by 100. Scoring procedures described in the test manual were followed when encountering instruments with missing items for constructs Martin ( 2012) provided an additi onal formula to use when one question per construct was left unanswered, such as the following example: Self Belief : ((Q13 + Q 23 + Q33 + Q40) / 15 ) X 100) The following is an explanation of the formula: Q13, Q23, Q33, Q40 represent the four questions f rom the instrument which pertain to the self belief construct which were added together. T he sum was then divided by 15 to reflect the missing question and multiplied by 100. Those instruments with more than one missing answer for each construct were elimi nated from the study.

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79 Raw scores were calculated for each construct for each participant. The mean s and standard deviation s w ere then calculated for each construct with all participants, as well as, by gender, age, and grade level. Global booster thought scores were calculated following a formula provided by Martin (2012) in the MES JS test user manual, such as the example that follows: (SB + V + LF) / 3 The following is an explanation of the formula: SB represents the self belief raw score, V represen ts the valuing raw score, and LF represents the learning focus raw score. The sum was divided by 3 to represent the average of the adaptive motivational thoughts. Global muffler scores were calculated following a formula provided by Martin (2012) in the M ES JS test user manual, such as the example that follows: (A+ FA+ UC) / 3 The following is an explanation of the formula: A represents the anxiety raw score, FA represents the failure avoidance raw score, and UC represents the uncertain control raw score The sum was divided by 3 to represent the average of the maladaptive motivational thoughts. Global booster thought and global muffler scores were calculated for each participant. The mean s and standard deviation s w ere then calculated for global booster thought and global muffler scores for all participants, as well as, by gender, age, and grade level. Data were analyz ed using descriptive statistics including the mean and standard deviations. Assumptions of central tendency were met, as the MES JS collec ted interval

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80 data using a 5 point Likert type scale (Ary et al., 2010). The test user manual instructions were followed when inter preting scores. Raw scores we re evaluated based off of an average of 100 for junior school students (Martin, 2012). For adapti ve motivational scores (self belief, valuing, and learning focus) higher scores we re considered better, and f or maladaptive motivational scores (anxiety, failure avoidance, and uncertain control) lower scores wer e considered better (Martin, 2012). Researc h Objective Two Research objective two was to identify middle school agricultural education reported perceptions of engagement in learning. Data were collected using the MES JS to accomplish this objective. Instrument scoring procedures giv en by Martin (2012) in the MES JS test user manual we re used to score the instrument. Scores for each question were entered into Microsoft Excel to formulate raw scores for each construct. Raw scores were calculated using a formula provided by Martin (2012 ), such as the following example. Task M anagement : ((Q3 + Q17 + Q 32 + Q44 ) / 20) X 100) The following is a n explanation of the formula: Q3, Q17 Q3 2, Q44 represent the four questions from the instrument which pertain to the task management construct wh ich were added together. The sum was then divided by 20 and multiplied by 100. Scoring procedures described in the test manual were followed when encountering instruments with missing items for constructs. Martin (2012) provided an additional formula to u se when one question per construct was left unanswered, such as the following example: Task M anagement : ((Q3 + Q17 + Q32 + Q44) / 15) X 100)

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81 The following is an explanation of the formula: Q3, Q17, Q32, Q44 represent the four questions from the instrume nt which pertain to the task management construct which were added together. The sum was then divided by 15 to reflect the missing question and multiplied by 100. Those instruments with more than one missing answer for each construct were eliminated from t he study. Raw scores were calculated for each construct for each participant. The means and standard deviations were then calculated for each construct with all participants, as well as, by gender, age, and grade level. Global booster engagement scores w ere calculated following a formula provided by Martin (2012) in the MES JS test user manual, such as the example that follows: ( PL N + TM + P ) / 3 The following is an explanation of the formula: PL N represents the planning raw score, TM represents the ta sk management raw score, and P represents the persistence raw score. The sum was divided by 3 to represent the average of the adaptive engagement behaviors Global guzzler scores were calculated following a formula provided by Martin (2012) in the MES JS test user manual, such as the example that follows: ( D + SS ) / 2 The following is an explanation of the formula: D represents the disengagement raw score and SS represents the self sabotage raw score. The sum was divided by 2 to represent the average of t he maladaptive engagement behaviors Global booster engagement and global guzzler scores were calculated for each participant. The mean s and standard deviation s w ere then calculated for global booster

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82 engagement and global guzzler scores for all participa nts, as well as, by gender, age, and grade level. Data were analyzed using descriptive statistics including the mean and standard deviations. Assumptions of central tendency were met as the MES JS collected interval data using a 5 point Likert type scale (Ary et al., 2010). The test user manual instruct ions were followed when interpre ting scores. Raw scores we re evaluated based off of an average of 100 for junior school students (Martin, 2012). For adaptive engagement scores (planning, task management, and persistence) higher scores were considered better, and f or maladaptive engagement scores (disengagement and self sabotage) lower scores we re considered better (Martin, 2012). Research Objective Three Research objective three was to examine the relations hip between middle school level), and self reported perceptions of motivation and engagement in learning. Data were collected using the MES JS to accomplish this objective Construct raw scores and global scores calculated according to formulas provided by Martin (2012) i n the MES JS test user manual as describ ed in objectives one and two wer e used to run correlations. Pearson r correlation s w ere used to determine the re lationship between age grade level and engagement and motivation in learning as these variables contain continuous data. This study aimed to collect data on participants operationalized as dents in the sample fell they are students attending middle school.

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83 Point biserial correlations were calculated between gender and engagement and motivation in learn ing as it is dichotomous data (Ary et al., 2010). This study meets the assumptions of Pearson r correlations and biserial correlations as data were collected using interval data from the MES JS and were assumed to be normally distributed. Chapter Summar y Chapter three discussed the details of the research methodology of this study including the research design, population, instrumentation, data collection, and data analysis. This study used a descriptive/correlational research design to gather informati perceptions of motivation and engagement (dependent (independent variable), and to determine relationships between the independent and dependent vari education students in Florida. A convenience sample of students w as taken from six schools within Florida. The MES perceptions of motivation and engagement in learning. Data were analyzed using SPSS version 17.0 for Windows XP software. Descriptive statistics including mean s range, frequencies, and standard deviations were used to analyze data concerning research objectives one and two and Pearson r and biserial point correlations were used to analyze the relationships between variables in objective three The results of the data analysis will be discussed in chapter four.

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84 CHAPTER 4 RESULTS The problem of the current drop ou t epidemic facing the United States was introduced in chapter 1 of this study. Student motivation and engagement were introduced as constructs that can potentially decrease student dropout rates in the United States. Additionally, definitions of key terms, the purpose of the study, limitations and assumptions, and the objectives of the study were discussed. The purpose of this study was to ascertain the perspectives of agricultural education middle school students on motivation and engagement in learning. T he specific objectives of this study were to: 1) reported perceptions of motivation to learn, 2) reported perceptions of engagement in lea rning, 3) Examine the relationships between middle school agricultural education demographic characteristics ( age, gender and grade level), and their perceptions of motivation to learn and engagement in learning. Chapter 2 discussed the foundatio nal theories of this study including student dropout, adolescent cognition theories, theories of motivation, theories of engagement, and motivation and engagement theory. A conceptual model of motivation and engagement was also presented based on these the ories. Additionally, empirical literature was provided to reinforce the conceptual model of motivation and engagement. Chapter 3 discussed the research methodology of this study. Research design, population, instrumentation, data collection procedures, an d data analysis were also described in this chapter. Chapter 4 discusses the results of the data analysis listed by objective.

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85 Response Rates Twelve agricult ural education teachers located in North Florida were invited to participate in this study. Six of the twelve teachers agreed to participate in the study. Thus, the studen ts within the classrooms of th e teachers who agreed to participate became the acc epting population of the study. Based on enrollment figures an estimated 700 instruments we re sent t o participants among the six educators who agreed to participate in the study. Students were administered the MES JS from December 2012 January 2013. A total of 218 instruments were received back from participants; however only 213 were included in the ana lysis of this study as five instruments were incomplete. Post Hoc Reliability of Instruments e a post hoc reliability of .79 of the instrument used in this study. The MES JS (Lifelong Achievement Group, 2012) mea sured student motivation through three adaptive cognitive dimensions (self belief, learning focus, and valuing) and three maladaptive cognitive dimensions (uncertain control, failure avoidance, and anxiety) (Lifelong Achievement Group, 2012). The MES JS me asured student engagement through three adaptive behaviors (persistence, planning, and task management) and two maladaptive behavior dimensions (self sabotage and disengagement) (Lifelong Achievement Group, 2012). Description of Population The population w as described using age, gender, and grade level. An overview of the descriptive statistics is given in Table 4 1.

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86 Gender The majority of students were female (51.6%) ; 47.4% were males A small portion of students (.9%) did not report their gender (Table 4 1) Age Age of p articipants was categorized as ages 11, 12, 13, 14, 15, and 16. The largest group of participants w as 13 years old (38.0% ). The second largest group was 12 years old (28.6%), followed by 14 years o ld (19.2 %), 11 years old (10.8 % ), 15 y ears old (2.3 %), and 16 years old (.5 %). A small portion (.5%) of participants did not report their age (Table 4 1) Grade Level largest group of participants was in the 8 th grade (37.6 %), followed by 7 th grade (36.6%), and 6 th grade (24.9 %). A small portion (.9%) of students did not report their grade level (Table 4 1). Table 4 1 Descriptive S tatistics of the S ample ( n = 213) Frequency ( f ) Percent (%) Gender Male 101 47 .4 Female 110 51.6 Not Reported 2 .9 Age 11 23 10.8 12 61 28.6 13 81 38.0 14 41 19.2 15 5 2.3 16 1 .5 Not Reported 1 .5

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87 Table 4 1. Continued Frequency ( f ) Percent (%) Grade Level 6 53 24.9 7 78 36.6 8 80 37.6 Not Reported 2 .9 Ob jective One Objective 1 was to identify self reported perceptions of motivation to learn (See Table 4 2). Students were asked to complete the MES JS which measured the constructs of adaptive cognitive dimensi ons (self belief, learning focus, and valuing) and maladaptive cognitive dimensions (uncertain control, failure avoidance, and anxiety) (Lifelong Achievement Group, 2012).There was a total of 213 useable responses. Constructs were measured usin g a Likert t ype scale of 1 5, with 1 being s trongly d isagree to 5 s trongly a gree ( Martin 2012). Means for adaptive cognitive c onstructs were self belief 83.05 (SD = 12.4 n = 213), l earning focus 83.24 (SD = 13.1 n = 213) and valuing 80.92 (SD = 14.9 n = 213). Mea ns for maladaptive cognitive constr ucts were uncertain control 41. 37 (SD = 15.6 n = 213), fail ure avoidance 55.27 (SD = 21.6 n = 213), and anxiety 62.78 (SD = 17.3 n = 213). Table 4 2 Adaptive and M aladaptive M otivation C onstruct M eans ( n = 213) R ange Low High Mean Std Deviation Adaptive Construct Self Belief 40 100 83.05 12.4 Learning Focus 40 100 83.24 13.1 Valuing 30 100 80.92 14.9

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88 Table 4 2. Continued Range Low High Mean Std Deviation Maladaptive Construct Uncertai n Control 20 87 41.37 15.6 Failure Avoidance 20 100 55.27 21.6 Anxiety 20 100 62 .78 17.3 Note Scores are based on an average of 100 for junior school students Higher scores are considered better for adaptive constructs and lower scores are considered better for maladaptive constructs (Martin, 2012). Mean construct scores for adaptive and maladaptive constructs were also calculated by age (See Table 4 3), grade level (See Table 4 4), and gender (See Table 4 5). Means for adaptive constructs for 11 y ear old participants were self belief 83.48 (SD = 17.6 n = 23), learning focus 83.91 (SD = 13.3 n = 23) and valuing 79.64 (SD = 17.5 n = 23). Means for maladaptive constructs for 11 y ea r old participants were unce rtain control 42.68 (SD = 19.3 n = 2 3 ) failure avoidance 50.43 (SD = 23.6 n = 23) and anxiety 63.26 (SD = 17.6 n = 23). Means for adaptive constructs for 12 year old participants wer e self belief 84.67 (SD = 10. 6 n = 61), l earning focus 84.02 (SD = 13.3 n = 61) and valuing 81.89 (SD = 1 4.6 n = 61). Means for maladaptive constructs for 12 y ea r old participants were unce rtain control 41.72 (SD = 15.6 n = 61 ), failure avoidance 54.51 (SD = 20. 5 n = 61) and anxiety 62. 38 (SD = 1 7.2 n = 61). Means for adaptive constructs for 13 year old participants wer e self belief 82.90 (SD = 13.0 n = 81), learning focus 82.90 (SD = 13.6 n = 81) and valuing 80.60 (SD = 15.8 n = 81). Means for maladaptive constructs for 13 y ea r old participants were unce rtain control 39.63 (SD = 14.3 n = 81 ), failur e avoidance 53.60 (SD = 22.0 n = 81) and anxiety 60.68 (SD = 17.2 n = 81). Means for adaptive constructs for 14 year old participants wer e self belief 80.37 (SD = 10.0 n = 41), l earning focus 81.46 (SD = 12.5 n = 41), and valuing 80.61

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89 (SD = 11.9 n = 41). Means for maladaptive constructs for 14 y ea r old participants were unce rtain control 41.22 (SD = 15.7 n = 41 ), failure avoidance 60.12 (SD = 21.0 n = 41) and anxiety 65.28 (SD = 17.3 n = 41). Means for adaptive constructs for 15 year old particip ants wer e self belief 85.00 (SD = 13.6 n = 5), l earning focus 89.00 (SD = 11.4 n = 5) and valuing 81.00 (SD = 15.9 n = 5). Means for maladaptive constructs for 15 y ea r old participants were unc ertain control 50.00 (SD = 9.3 n = 5 ), failure avoidance 7 0.00 (SD = 21.5 n = 5 ), and anxiety 78.00 (SD = 10.9 n = 5). Means for adaptive constructs for 16 year old participants were self belief 80 ( n = 1), learning focus 85 ( n = 1), and valuing 70 ( n = 1). Means for maladaptive constructs for 16 y ea r old parti cipants were uncertain control 60 ( n = 1 ), failure avoidance 55 ( n = 1), and anxiety 45 ( n = 1). Table 4 3 Adaptive and Maladaptive Motivation Construct Age Means Range Low High Mean Std Deviation Age 11 ( n = 23) Adaptive Construct Self Belief 40 100 83.48 17.6 Learning Focus 50 100 83.91 13.3 Valuing 40 100 79.64 17.5 Maladaptive Construct Uncertain Control 20 87 42.68 19.3 Failure Avoidance 20 100 50.43 23.6 Anxiety 25 95 63.26 17.6 Age 12 ( n = 61) Adaptive Construct Self Belief 60 100 84. 67 10. 6 Learning Focus 50 100 84.02 13.3 Valuing 30 100 81.89 14.6 Maladaptive Construct Uncertain Control 20 80 41.72 15.6 Failure Avoidance 20 100 54.51 20. 5 Anxiety 30 100 62. 38 17.2

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90 Table 4 3. Continued Range Low High Mean Std Deviation Age 13 ( n = 81) Adaptive Construct Self Belief 50 100 82.90 13.0 Learning Focus 40 100 82.90 13.6 Valuing 30 100 80.60 15.8 Maladaptive Construct Uncertain Control 20 75 39.63 14.3 Failure Avoidance 20 100 53.60 22.0 Anxiety 20 95 60.68 17.2 Age 14 ( n = 41) Adaptive Construct Self Belief 60 100 80.37 10.0 Learning Focus 55 100 81.46 12.5 Valuing 55 100 80.61 11.9 Maladaptive Construct Uncertain Control 20 75 41.22 15.7 Failure Avoidance 20 100 60.12 21.0 Anxiety 20 95 65.28 17.3 Age 15 ( n = 5) Adaptive Construct Self Belief 65 100 85.00 13.6 Learning Focus 75 100 89.00 11.4 Valuing 60 100 81.00 15.9 Maladaptive Construct Uncertain Control 40 65 50.00 9.3 Failure Avo idance 45 95 70.00 21.5 Anxiety 60 86 78.00 10.9 Age 16 ( n = 1) Adaptive Construct Self Belief 80 80 80 ---------Learning Focus 85 85 85 ---------Valuing 70 70 70 ---------Maladaptive Construct Uncertain Control 60 60 60 --------Failure Avoidance 55 55 55 ---------Anxiety 45 45 45 ---------Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for adaptive constructs and lower scores are considered better for maladapt ive constructs (Martin, 2012).

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91 Means for adaptive constructs for 6 th grade participants wer e self belief 83.87 (SD = 13.8 n = 53), learning focus 83.96 (SD = 12 .9 n = 53) and valuing 86.64 (SD = 16.9 n = 53). Means for maladaptive constructs for 6 th grade participants were unce rtain control 42.33 (SD = 18.2 n = 5 3 ), failure avoidance 51.70 (SD = 22. 4 n = 53) and anxiety 62.83 (SD = 1 6.9 n = 53). Means for adaptive constructs for 7 th grade participants wer e self belief 84.04 (SD = 11.2 n = 78), l e arning focus 84.68 (SD = 13.0 n = 78) and valuing 81.60 (SD = 14.2 n = 78). Means for maladaptive constructs for 7 th grade participants were unce rtain control 41.45 (SD = 13.9 n = 78 ), failure avoidance 56.99 (SD = 22.2, n = 78) and anxiety 62.20 (SD = 18.2 n = 78). Means for adaptive constructs for 8 th grade participants wer e self belief 81.31 (SD = 12.4 n = 80), learning focus 81.31 (SD = 13.7 n = 80) and valuing 78.94 (SD = 14.0 n = 80). Means for maladaptive constructs for 8 th grade participan ts were unce rtain control 40.25 (SD = 15.0 n = 80 ), failure avoidance 55.77 (SD = 20.7 n = 80) and anxiety 63.19 (SD = 16.9 n = 80). Table 4 4 Adaptive and Maladaptive Motivation Construct Grade Level Means Range Low High Mean Std Deviation G rade 6 ( n = 5 3) Adaptive Construct Self Belief 40 100 83.87 13. 8 Learning Focus 50 100 83.96 12.9 Valuing 35 100 82.6 4 1 6.9 Maladaptive Construct Uncertain Control 20 87 42.33 18.2 Failure Avoidance 20 100 51.7 0 22. 4 Anxiety 25 100 62. 83 1 6.9 Grade 7 ( n = 78) Adaptive Construct Self Belief 55 100 84.04 11.2 Learning Focus 50 100 84.68 13.0 Valuing 30 100 81.60 14.2

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92 Table 4 4. Continued Range Low High Mean Std Deviation Maladaptive Construct Uncertain Control 2 0 75 41.45 13.9 Failure Avoidance 20 100 56.99 22.2 Anxiety 20 95 62.20 18.2 Grade 8 ( n = 80) Adaptive Construct Self Belief 50 100 81.31 12.4 Learning Focus 40 100 81.31 13.7 Valuing 30 100 78.94 14.0 Maladaptive Construct Uncertain Control 20 75 40.25 15.0 Failure Avoidance 20 100 55.77 20.7 Anxiety 80 20 63.19 16.9 Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for adaptive constructs and lower scores are considered be tter for maladaptive constructs (Martin, 2012). Means for adaptive constructs for male participants wer e self belief 82.92 (SD = 11.8 n = 101), l earning focus 81.63 (SD = 12.9 n = 101 ), and valuing 79.88 (SD = 16.0 n = 101). Means for maladaptive cons tructs for male participants were uncertain control 40.97 (SD = 15.1, n = 101 ), failure avoidance 54.90 (SD = 21.0, n = 101), and anxiety 57.79 (SD = 16.9, n = 101). Means for adaptive constructs for female participants were self belief 83.00 ( SD = 12.9, n = 110), learning focus 84.68 (SD = 13.2, n = 110), and valuing 81.74 (SD = 1 3 .8 n = 11 0). Means for maladaptive constructs for female participants were unce rtain control 41.44 (SD = 15.8 n = 110 ), failure avoidance 55.47 (SD = 22.4 n = 110) and anxiet y 67.27 (SD = 16.5 n = 110). Table 4 5 Adaptive and Maladaptive Motivation Construct Gender Means Range Low High Mean Std Deviation Male ( n = 101) Adaptive Construct Self Belief 55 100 82.92 11.8

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93 Table 4 5. Continued Range Low Hi gh Mean Std Deviation Learning Focus 40 100 81.63 12.9 Valuing 30 100 79.88 16.0 Maladaptive Construct Uncertain Control 20 87 40.97 15.1 Failure Avoidance 20 100 54.90 21.0 Anxiety 20 100 57.79 16.9 Female ( n = 110) Adaptive Construct Self Belief 40 100 83.00 12.9 Learning Focus 45 100 84.68 13.2 Valuing 35 100 81.74 13.8 Maladaptive Construct Uncertain Control 20 75 41.44 15.8 Failure Avoidance 20 100 55.47 22.4 Anxiety 25 95 67.27 16.5 Note Scores are based on an averag e of 100 for junior school students. Higher scores are considered better for adaptive constructs and lower scores are considered better for maladaptive constructs (Martin, 2012). Global mean construct scores were also calculated for adaptive and maladapt ive motivation constructs (See Table 4 6). A Global Booster Thought m ean score of 82.40 (SD = 11. 3 n = 213) was calculated using the average mean scores of adaptive cognitive constructs (self belief, learning focus, and valuing). A Global Muffler m ean sco re of 53.14 (SD = 13.7 n = 213) was calculated using the average mean scores of maladaptive cognitive constructs (uncertain control, failure avoidance, and anxiety). Table 4 6 Adaptive and Maladaptive Global Motivation Construct Means ( n = 213) Range Low High Mean Std Deviation Global Booster Thought 43.33 100.00 82.40 11.3 Global Muffler 23.33 86.66 53.14 13.7 Note Scores are based on an average of 100 for junior school students Higher scores are considered better for global booster thought a nd global booster engagement scores, and lower scores are considered better for global muffler and global guzzler scores (Martin, 2012).

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94 Global mean construct scores for adaptive and maladaptive motivation constructs were also calculated by age (See Tabl e 4 7), grade level (See Table 4 8), and gender (See Table 4 9). The mean Global Booster Thought score for 11 year old participants wa s 82.34 (SD = 14.5 n = 23 ) and the mean Global Muffler was 52.12 (SD = 16.8 n = 23). The mean Global Booster Thought sco re for 12 year old part icipants was 83.52 (SD = 10.4 n = 61 ) and the mean Global Muffler was 52 .87 (SD = 13. 6 n = 61). The mean Global Booster Thought score for 13 year old par ticipants was 82.13 (SD = 12.0 n = 81 ) and the mean Global Muffler was 51.30 (SD = 12.7 n = 81). The mean Global Booster Thought score for 14 year old par ticipants was 80.81 (SD = 8.7 n = 4 1 ) and the mean Global Muffler was 55.54 (SD = 13.1 n = 41). The mean Global Booster Thought score for 15 year old participants was 8 5 .00 (SD = 12.9 n = 5 ) and the mean Globa l Muffler was 66.00 (SD = 12.45 n = 5). The mean Global Booster Thought score for 16 year old participants was 78.33 ( n = 1 ) and the mean Global Muffler mean was 53.33 ( n = 1). Table 4 7 Adaptive and Maladaptive Global Motivation Construct Age Means Range Low High Mean Std Deviation Age 11 ( n = 23) Global Booster Thought 43.33 100.00 82.34 14.5 Global Muffler 26.66 81.66 52.12 16.8 Age 12 ( n = 61) Global Booster Thought 56.66 10 0.00 83.52 10.4 Global Muffler 30.00 86.66 52.87 13. 6 Age 13 ( n = 81) Global Booster Thought 46.66 100.00 82.13 12.0 Global Muffler 23.33 83.33 51.30 12.7 Age 14 ( n = 41) Global Booster Thought 60.00 98.33 80.81 8.7 Global Muffler 31.66 83.33 55.54 13.1

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95 Ta ble 4 7. Continued Range Low High Mean Std Deviation Age 15 ( n = 5) Global Booster Thought 66.66 98.33 85.00 12.9 Global Muffler 51.66 81.66 66.00 12.4 Age 16 ( n = 1) Global Booster Thought 78.33 78.33 78.33 --------Global Muffler 53. 33 53.33 53.33 --------Note Scores are based on an average of 100 for junio r school students Higher scores are considered better for global booster thought and global booster engagement scores, and lower scores are considered better for global muffler and global guzzler scores (Martin, 2012). The mean Global Booster Thought score for 6 th grade part icipants was 83.49 (SD = 12.7 n = 53 ) and the mean Globa l Muffler was 52.29 (SD = 15. 6 n = 53). The mean Global Booster Thought score for 7 th grade part i c ipants was 83.44 (SD = 10.2 n = 78 ) and the mean Global Muffler was 53.54 (SD = 13.6 n = 78). The mean Global Booster Thought score for 8 th grade participants was 80.52 (SD = 11 .1 n = 80 ) and the mean Global Muffler was 53.06 (SD = 12.6 n = 80). Tabl e 4 8 Adaptive and Maladaptive Global Motivation Construct Grade Level Means Range Low High Mean Std Deviation Grade 6 ( n = 53) Global Booster Thought 43.33 100.00 83.49 12.7 Global Muffler 26.66 83.33 52.29 15.6 Grade 7 ( n = 78) Global Booster Thought 55.00 100.00 83.44 10.2 Global Muffler 25.00 86.66 53.54 13.6 Grade 8 ( n = 80) Global Booster Thought 46.66 100.00 80.52 11.1 Global Muffler 23.33 81.66 53.06 12.6 Note Scores are based on an average of 100 for junior school stud ents. Higher scores are considered better for global booster thought and global booster engagement scores, and lower scores are considered better for global muffler and global guzzler scores (Martin, 2012).

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96 The mean Global Booster Thought score for male p art icipants was 81.48 (SD = 11.4 n = 1 01 ) and the mean Global Muffler was 51.22 (SD = 13.3 n = 101). The mean Global Booster Thought score for female part icipants was 83.14 (SD = 11.1 n = 110 ) and the mean Global Muffler was 54.72 (SD = 13.9 n = 110). Table 4 9 Adaptive and Maladaptive Global Motivation Construct Gender Means Range Low High Mean Std Deviation Males ( n = 101) Global Booster Thought 46.66 100.00 81.48 11. 4 Global Muffler 28.33 83.33 51. 22 13. 3 Female ( n = 101) Global Booster Thought 43.33 100.00 83.14 11.1 Global Muffler 23.33 86.66 54.72 13.9 Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for global booster thought and global booster engagement scores, an d lower scores are considered better for global muffler and global guzzler scores (Martin, 2012). Objective Two Objective 2 was to identify self reported perceptions of engagement in learning of middle school agricultural education students (See Table 4 10). Students were asked to complete the MES JS which measured the constructs of adaptive engagement b ehaviors (persistence, planning, and task management) and maladaptive engagement behavior dimensions (self sabotage and disengagement) (Lifelong Achievem ent Group, 2012).There w as a total of 213 useable responses. Constructs were measured using a Likert type scale of 1 to 5; with 1 being s trongly disagree to 5 s trongly a gree ( Martin 2012). Means for adaptive engagement constructs wer e persistence 73.30 (S D = 13.9 n = 213), ta sk management 75.02 (SD = 16.4 n =213), and planning 68.22 (SD = 17.3 n = 213). Means for maladaptive engagement constructs were disengagement 35.33 (SD = 13.9, n = 213) and self sabotage 36.9 2 (SD = 16.3 n = 213).

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97 Table 4 10 A daptive and Maladaptive Engagement Construct Means ( n = 213) Range Low High Mean Std Deviation Adaptive Construct Persistence 25 100 73.30 13.9 Task Management 30 100 75.02 16.4 Planning 20 100 68.22 17.3 Maladaptive Construct Disengage ment 20 85 35.33 13.9 Self Sabotage 20 95 36.92 16.3 Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for adaptive constructs and lower scores are considered better for maladaptive constructs (M artin, 2012). Means for adaptive and maladaptive engagement constructs were also calculated by age (See Table 4 11), grade level (See Table 4 12), and gender (See Table 4 13). Means for adaptive engagement constructs for 11 year old participants wer e per sistence 74.49 (SD = 19.5 n = 23), task management 76.52 (SD = 19.0 n = 23), and planning 67.39 (SD = 18.8 n = 23). Maladaptive engagement constructs for 11 year old participants were disengagement 31.96 (SD = 16.3 n = 23) and self sabotage 31.88 (SD = 20.3 n = 23). Means for adaptive engagement constructs for 12 year old participants wer e persistence 74.62 (SD = 11.9 n = 61), ta sk management 78.28 (SD = 14.3 n = 61), and planning 68.61 (SD = 17.1 n = 61). Maladaptive engagement constructs for 12 ye ar old participants were disengag ement 33.20 (SD = 12.3 n = 61) and self sabotage 32.92 (SD = 13.6 n = 61). Means for adaptive engagement constructs for 13 year old participants wer e persistence 71.89 (SD = 14.9 n = 81), ta sk management 73.83 (SD = 17.6 n = 81), and planning 68. 09 (SD = 17.8 n = 81). Maladaptive engagement constructs for 13 year old participants were disengagement 36.21 (SD = 14.5 n = 81) and self sabotage 38.27 (SD = 16.4 n = 81). Means for adaptive engagement constructs for 14 year old participants were pe rsistence 72.68

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98 (SD = 11.2 n = 41), ta sk management 71.59 (SD = 15.9 n = 41), and planning 68.54 (SD = 16.6 n = 41). Maladaptive engagement constructs for 14 year old participants were disengagement 36.99 (SD = 13.1 n = 41) and self sabotage 41.4 2 (SD = 15.5 n = 41). Means for adaptive engagement constructs for 15 year old participants wer e persistence 82.00 (SD = 10.3 n = 5), t ask management 81.00 (SD = 8.2 n = 5), and planning 71.00 (SD = 18.8 n = 5). Maladaptive engagemen t constructs for 15 year old participants were disengagement 40.00 (SD = 12.7 n = 5) and self sabotage 37.00 (SD = 9.0, n = 5). Means for adaptive engagement constructs for 16 year old participants were persistence 60.00 ( n = 1), task management 50.00 ( n = 1), and planning 45.00 ( n = 1). Maladaptive engagement constructs for 16 year old participants were disengagement 65.00 ( n = 1) and self sabotage 65.00 ( n = 1). Table 4 11 Adaptive and Maladaptive Engagement Construct Age Means Range Low High M ean Std Deviation Age 11 ( n = 23) Adaptive Construct Persistence 25 100 74.49 19.5 Task Management 35 100 76.52 19.0 Planning 25 100 67.39 18.8 Maladaptive Construct Disengagement 20 75 31.96 16.3 Self Sabotage 20 85 31.88 20.3 Age 12 ( n = 61) Adaptive Construct Persistence 40 100 74.62 11.9 Task Management 35 100 78.28 14.3 Planning 20 100 68.61 17.1 Maladaptive Construct Disengagement 20 80 33.20 12.3 Self Sabotage 20 65 32.92 13.6

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99 Table 4 11. Continued Range Low High Mean Std Deviation Age 13 ( n = 81) Adaptive Construct Persistence 30 100 71.89 14.9 Task Management 30 100 73.83 17.6 Planning 25 100 68.09 17.8 Maladaptive Construct Disengagement 20 85 36.21 14.5 Self Sabotage 20 95 38.2 7 16.4 Age 14 ( n = 41) Adaptive Construct Persistence 50 100 72.68 11.2 Task Management 40 100 71.59 15.9 Planning 30 100 68.54 16.6 Maladaptive Construct Disengagement 20 75 36.99 13.1 Self Sabotage 20 65 41.42 15.5 Age 15 ( n = 5) Adaptive Construct Persistence 75 100 82.00 10.3 Task Management 75 95 81.00 8.2 Planning 50 100 71.00 18.8 Maladaptive Construct Disengagement 20 55 40.00 12.7 Self Sabotage 25 50 37.00 9.0 Age 16 ( n = 1) Adaptive Construct Pe rsistence 60 60 60 ---------Task Management 50 50 50 ---------Planning 45 45 45 ---------Maladaptive Construct Disengagement 65 65 65 ---------Self Sabotage 65 65 65 ---------Note Scores are based on an average of 100 for junior schoo l students Higher scores are considered better for adaptive constructs and lower scores are considered better for maladaptive constructs (Martin, 2012). Means for adaptive engagement constructs for 6 th grade participants were persistence 75.94 (SD = 16. 3, n = 53), task management 77.80 (SD = 16.8, n = 53), and planning 69.25 (SD = 18.7, n = 53). Maladaptive engagement constructs for 6 th grade

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100 participants were disengagement 34.06 (SD = 14.3, n = 53) and self sabotage 34.18 (SD = 17.5 n = 53). Means for adaptive engagement constructs for 7 th grade participants we re persistence 74.42 (SD = 11.9 n = 78), ta sk management 77.99 (SD = 14.7 n = 78), and planning 70.32 (SD = 17.2 n = 78). Maladaptive engagement constructs for 7 th grade participants were disen g agement 33.14 (SD = 13.7 n = 78) and self sabotage 35.77 (SD = 17.4 n = 78). Means for adaptive engagement constructs for 8 th grade participants were persistence 70.42 (SD = 13.9 n = 80), ta sk management 70.48 (SD = 17.0 n = 80), and planning 66. 00 (S D = 16.3 n = 80). Maladaptive engagement constructs for 8 th grade participants were disengagement 38.44 (SD = 13.6 n = 80) and self sabotage 40.10 (SD = 14.0 n = 80). Table 4 12 Adaptive and Maladaptive Engagement Construct Grade Level Means Range Low High Mean Std Deviation Grade 6 ( n = 5 3) Adaptive Construct Persistence 25 100 75.94 16.3 Task Management 35 100 77.80 16.8 Planning 20 100 69.25 18.7 Maladaptive Construct Disengagement 20 75 34.06 14.3 Self Sabotage 20 85 34.1 8 17.5 Grade 7 ( n = 78) Adaptive Construct Persistence 45 100 74.42 11.9 Task Management 35 100 77.99 14.7 Planning 25 100 70.32 17.2 Maladaptive Construct Disengagement 20 85 33.14 13.7 Self Sabotage 20 95 35.77 17.4 Grade 8 ( n = 80) Adaptive Construct Persistence 30 100 70.42 13.9 Task Management 30 100 70.48 17.0 Planning 30 100 66.00 16.3

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101 Table 4 12. Continued Range Low High Mean Std Deviation Maladaptive Construct Disengagement 20 75 38.44 13.6 Self Sabot age 20 70 40.10 14.0 Note Scores are based on an average of 100 for junior school students Higher scores are considered better for adaptive constructs and lower scores are considered better for maladaptive constructs (Martin, 2012). Means for adaptiv e engagement constructs for male participants were persistenc e 72.77 (SD = 14.0 n = 101), ta sk management 73.33 (SD = 16.8 n = 101), and planning 67.38 (SD = 17.4 n = 101). Maladaptive engagement constructs for male participants were disengagement 38.12 (SD = 14.3 n = 101) and self sabotage 37.49 (SD = 15. 6 n = 101). Means for adaptive engagement constructs for female participants wer e persistence 73.76 (SD = 14.0 n = 110), ta sk management 76.71 (SD = 16.1 n = 110), and planning 69.36 (SD = 17.2 n = 110). Maladaptive engagement constructs for female participants were disengagement 32.86 (SD = 13.2 n = 110) and self sabotage 36.58 (SD = 17.0 n = 110). Table 4 13 Adaptive and Maladaptive Engagement Construct Gender Means Range Low High Mean Std Deviation Male ( n = 101) Adaptive Construct Persistence 40 100 72.77 14.0 Task Management 35 100 73.33 16.8 Planning 20 100 67.38 17.4 Maladaptive Construct Disengagement 20 80 38.12 14.3 Self Sabotage 20 75 37.49 15.6 Female ( n = 110) Adaptive Construct Persistence 25 100 73.76 14.0 Task Management 30 100 76.71 16.1 Planning 25 100 69.36 17.2

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102 Table 4 13. Continued Range Low High Mean Std Deviation Maladaptive Construct Disengagement 20 85 32.86 13.2 Self Sabotage 20 95 36.58 17.0 Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for adaptive constructs and lower scores are considered better for maladaptive constructs (Martin, 2012). Global mean construct scores were also calculated for adaptive and maladaptive engagement constructs (See Table 4 14). A Global Booster Engagement me an score of 72.18 (SD = 13.3 n = 213) was calculated using the average mean scores of adaptive engagement constructs ( persistence, task management, and planning). A Global Guzzler m ean score of 36.12 (SD = 13.3 n = 213) was calculated using the average mean scores of maladaptive engagement constructs (disengagement and self sabotage). Table 4 14 Adaptive and Maladapti ve Global Engagement Construct Means ( n = 213) Range Low High Mean Std Deviation Global Booster Engagement 32 100 72.18 13.3 Global Guzzler 20 90 36.12 13.3 Note Scores are based on an average of 100 for junior school students Higher scores are c onsidered better for global booster thought and global booster engagement scores, and lower scores are considered better for global muffler and global guzzler scores (Martin, 2012). Global mean construct scores for adaptive and maladaptive engagement con structs were also calculated by age (See Table 4 5), grade level (See Table 4 16), and gender (See Table 4 17). The mean Global Booster Engagement score for 11 year old part icipants was 72.80 (SD = 16.0, n = 23 ) and the mean Global Guzzler was 31.92 (SD = 16.3 n = 23). The mean Global Booster Engagement score for 12 year old

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103 participants was 73.83 (SD = 12.1 n = 61 ) and the mean Global Guzzler was 33.06 (SD = 11.6 n = 61). The mean Global Booster Engagement score for 13 year old par ticipants was 72 .27 (S D = 14.3 n = 81 ) and the mean Global Guzzler was 37. 24 (SD = 13.5 n = 81). The mean Global Booster Engagement score for 14 year old par ticipants was 70.93 (SD = 11.4 n = 4 1 ) and t he mean Global Guzzler was 39.21 (SD = 11.7 n = 41). The mean Global Boos ter Engagement score for 15 year old par ticipants was 78.00 (SD = 11.9 n = 5 ) and the mean Globa l Guzzler was 38.50 (SD = 10.6 n = 5). The mean Global Booster Engagement score for 16 year old participants was 51.67 ( n = 1 ) and the mean Global Guzzler was 65.0 ( n = 1). Table 4 15 Adaptive and Maladaptive Global Engagement Construct Age Means Range Low High Mean Std Deviation Age 11 ( n = 23) Global Booster Engagement 40 97 72.80 16.0 Global Guzzler 20 72.5 31.92 16.3 Age 12 ( n = 61) Glo bal Booster Engagement 32 96 73.83 12.1 Global Guzzler 20 70 33.06 11.6 Age 13 ( n = 81) Global Booster Engagement 35 100 72.27 14.3 Global Guzzler 20 90 37.24 13.5 Age 14 ( n = 41) Global Booster Engagement 43 100 70.93 11.4 Global Guzzler 20 70 39.21 11.7 Age 15 ( n = 5) Global Booster Engagement 67 98 78.00 11.9 Global Guzzler 22.5 52.5 38.50 10.6 Age 16 ( n = 1) Global Booster Engagement 52 52 51.67 --------Global Guzzler 65 65 65.00 --------Note Scores are based on an ave rage of 100 for junior school students Higher scores are considered better for global booster thought and global booster engagement scores, and lower scores are considered better for global muffler and global guzzler scores (Martin, 2012).

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104 The mean Globa l Booster Engagement score for 6 th grade participants was 74.33 (SD = 14.8 n = 53 ) and the mean Global Guzzler was 34.11 (SD = 14.4 n = 53). The mean Global Booster Engagement score for 7 th grade par ticipants was 74.25 (SD = 12.4 n = 78 ) and the mean Gl obal Guzzler was 34.4 6 (SD = 13.4 n = 78). The mean Global Booster Engagement score for 8 th grade par ticipants was 68.97 (SD = 12.7 n = 80 ) and the mean Global Guzzler was 39.27 (SD = 11.9 n = 80). Table 4 16. Adaptive and Maladaptive Global Engagemen t Construct Grade Level Means Range Low High Mean Std Deviation Grade 6 ( n = 53) Global Booster Engagement 32 97 74.33 14.8 Global Guzzle r 20 72.5 34.11 14.4 Grade 7 ( n = 78) Global Booster Engagement 35 100 74.25 12.4 Global Guzzle r 20 90 34.46 13.4 Grade 8 ( n = 80) Global Booster Engagement 43 100 68.97 12.7 Global Guzzler 20 70 39.27 11.9 Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for global booster thought and gl obal booster engagement scores, and lower scores are considered better for global muffler and global guzzler scores (Martin, 2012). The mean Global Booster Engagement score for male par ticipants was 71.16 (SD = 13.4 n = 1 01 ) and th e mean Global Guzzler was 37.8 0 (SD = 13.2 n = 101). The mean Global Booster Engagement score for female par ticipants was 73.28 (SD = 13.3 n = 110 ) and the mean Globa l Guzzler was 34.72 (SD = 13.2 n = 110). Table 4 17 Adaptive and Maladaptive Global Engagement Construct G ender Means Range Low High Mean Std Deviation Males ( n = 101) Global Booster Engagement 32 100 71.16 13.4 Global Guzzler 20 72.5 37.80 13.2

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105 Table 4 17. Continued Range Low High Mean Std Deviation Female ( n = 101) Global Booster En gagement 35 100 73.28 13.3 Global Guzzler 20 90 34.72 13.2 Note Scores are based on an average of 100 for junior school students. Higher scores are considered better for global booster thought and global booster engagement scores, and lower scores are c onsidered better for global muffler and global guzzler scores (Martin, 2012). O bjective Three Objective 3 was to examine the relationships between middle school agricultural nd their perceptions of motivation to learn and engagement in learning. To accomplish this variables with continuous data and point biserial correlations were calculated fo r dichotomous data. The terminology presented by Davis (1971) was used to describe the magnitude of the associations among variables. A correlation of zero denotes no association between variables, whereas, a correlation of 1.00 denotes a perfect relations hip (Davis, 1971). Accordingly, correlations which fall in the range of .01 to .09 are considered to be negligible, .10 to .29 to be low, .30 to .49 to be moderate, .50 to .69 to be substantial, and .70 to .99 to be very high (Davis, 1971). Correlations w ere computed between global mean construct scores for adaptive/maladaptive motivation/engagement constructs and age, grade level, and gender. The matrixes of correlations are shown in Table 4 18 and Table 4 19. A low negative association was found between grade level and mean global booster thought scores (r = .11) (the average of self belief, valuing, and learning focus constructs). Students in higher grades tended to report slightly lower levels of booster

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106 thoughts. Low positive association was found be tween grade level and mean global guzzler scores (r = .15) (the average self sabotage and disengagement constructs). Students in higher grade s tended to report slightly higher levels of guzzler engagement. Low positive association s were found between age a nd mean global guzzler scores (r = .17) and mean global muffler scores (r = .14) (the average of anxiety, failure avoidance, and uncertain control constructs). Older students tended to report slightly higher levels of guzzler engagement and higher levels o f muffler thoughts. A low negative association was found between gender and mean global guzzler scores (r = .12), and a low positive association was found between gender and mean global muffler scores (r = .14). Males tended to report slightly higher leve ls of guzzler engagement, while females tended to report slightly higher levels of muffler thoughts. All other associations between mean global construct scores and age, grade level, and gender were found to be negligible. Investigating individual constru cts which comprise global scores (Table 4 20, T able 4 21) l ow negative associations were found between grade level and adaptive motivation constructs self belief ( r = .11 ), valuing ( r = .10 ), and maladaptive motivation construct uncertain control ( r = .10). Students in higher grade levels tend ed to report slightly lower self belief, uncertain control, and valuing. Low negative associations were also found between grade level and adaptive engagement constructs persistence ( r = .12) and task management ( r = .11). Students in higher grade levels tended to report slightly lower levels of task management and persistence. Low positive associations were found between grade level and maladaptive engagement constructs disengagement ( r = .12) and self sabotage ( r = .14). Students in higher grade levels

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107 tended to report slightly higher levels of self sabotage and disengagement. All other associations between grade level and adaptive/maladaptive motivation and engagement constructs were found to be negligible. Low positive associations were found between age and maladaptive motivational construct uncertain control ( r = .14 ) and maladaptive engagement construct self sabotage ( r = .19). Older students tended to report slightly higher levels of self sabotage and uncer tain control. All other associations between age and adaptive/maladaptive motivation and engagement constructs were found to be negligible. Low positive associations were found between gender and adaptive motivational construct learning focus ( r = .11) and maladaptive motivational construct anxiety ( r = .2 7 ). Females tended to report slightly higher levels of anxiety and learning focus. A low negative association was found between gender and maladaptive engagement construct disengagement ( r = .19). Males t ended to report slightly higher levels of disengagement. All other associations between gender and adaptive/maladaptive motivation and engagement constructs were found to be negligible. Table 4 18 Correlations Amo ng Global Motivation/Engagement Mean Cons truct Scores and Age/Grade Level ( n = 213) Grade Age Global Booster Thought Global Booster Engagement Global Muffler Global Guzzler Grade Pearson Correlation ----.11 .08 .03 .15 Age Pearson Correlation -------.05 .00 .14 .17 Table 4 19 Cor relations Among Global Motivation/Engagement Mean Construct Scores and Gender ( n = 213) Gender Global Booster Thought Global Booster Engagement Global Muffler Global Guzzler Gender Pearson Correlation ----.08 .05 .14 .12

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108 T able 4 20 Correlations Am ong Adaptive/Maladaptive Motivation/ Engagement Mean Construct Scores and Age/Grade Level ( n = 213) Grade Age Self Belief Persistence Learning Focus Valuing Task Management Planning Disengagement Self Sabotage Uncertain Control Failure Avoidance Anxiety Grade Pearson Correlation --.1 1 .12 .07 .1 0 .11 .01 .12 .14 .10 .02 .0 0 Age Pearson Correlation -.02 .00 .02 .08 .02 .00 .09 .19 .14 .08 .09 Table 4 21 Correlations A mong Adaptive/Maladaptive Motivation/ Engagement Mean Construct Sco res and Gender ( n = 213) Gender Self Belief Persistence Learning Focus Valuing Task Management Planning Disengagement Self Sabotage Uncertain Control Failure Avoidance Anxiety Gender Pearson Correlation .0 2 .03 .11 .07 .08 .02 .19 .04 .04 .02 .27

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109 Su mmary The findings of this study were presented in Chapter 4 organized around the objectives of this research. The objectives of the study were to: (a) identify self reported perceptions of motivation to learn in middle school agricultural education st udents, (b) identify self reported perceptions of engagement in learning in middle school agricultural education students, and (c) examine the relationship between demographic variables (age, gender, and grade level) and the self reported perceptions of m otivation to learn and engagement in learning in middle school agricultural education students. The findings presented in Chapter 4 will be described in greater detail in Chapter 5 in addition to conclusions, recommendations, and implications being present ed.

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110 CHAPTER 5 SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS The purpose of this study was to ascertain middle school agricultural education independent variables for this stu dy were gender, age, and grade level. The dependent perceptions of motivation and engagement in learning. Objectives The specific objectives of this study were to: 1) Identify middle school agricultural education reported perceptions of motivation to learn, 2) reported perceptions of engagement in learning, 3) Examine the relationships between middle school agricultural education dem ographic characteristics ( age gender and grade level), and their perceptions of motivation to learn and engagement in learning. Summary of Findings and Conclusions The findings of this study are organized by a description of the population followed by a summary of findings by objective. Description of Population Students of the six agricultural educators who agreed to participate in this study were used as the accepted population of this study. Students were enrolled in middle school agricultural educat ion courses in six counties in North Florida and completed the instrument between December 2012 and January 2013. The majority of the students were female (51.6%), and a large portion of students were 13 years old (38.0%) and in the 8 th grade (37.6%).

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111 Obj ective One The aim of objective one was to identify self reported perceptions of motivation to learn in middle school agricultural education students. Martin (2012) indicated that higher scores on adaptive motivational thoughts (self belief, valuing, and learning focus) were considered better than lower scores. M iddle school agricultural education students in this study tend ed to report higher global booster thoughts (self belief, valuing, and learning focus) than booster engagement behaviors Specifically 12 year old 6 th grade girls in the study tended to report the highest level s of global booster thoughts Examining the individual constructs which comprise global booster thoughts it was concluded that when reporting their self perceptions of motivation to learn the students in this study tended to report higher scores in the construct learning focus and reported the lowest scores in the construct valuing. Based on the findings it was concluded that students in this study reported higher scores in self be lief than learning focus at 12 years of age and tended to report the lowest scores of self belief at 14 years old. Additionally, male students in the study tended to report higher scores in the construct self belief than learning focus. The 6 th grade stud ents in this study tended to report the highest scores of valuing and 7 th grade students in this study tended to report t he highest scores of self belief and learning focus F emale students in this study tended to report higher scores of self belief, valu ing, and learning focus than males. Additionally, Martin (2012) indicated that lower scores on maladaptive motivational thoughts (uncertain control, failure avoidance, and anxiety) were considered better than higher scores. Middle school agricultural educ ation students in this study tended to report higher global muffler thoughts (anxiety, failure avoidance, and uncertain control)

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112 than guzzler engagement behavior s. Particularly, 14 year old 7 th grade females in this study tended to report the highest muffl er thoughts. Investiga ting individual constructs that encompass global muffler thoughts it was concluded that when reporting self perceptions of motivation to learn the students in this stud y tended to report the highest scores in anxiety and the lowest scores in uncertain control It was also concluded that female students i n this study tended to report higher scores of anxiety, uncertain control, and failure avoidance than males. M iddle school agricultural students in this study tended to report the hig hest scores of an xiety at 14 years old. Additionally, 14 year old 7th grade students in this study tended to report t he highest levels of failure avoidance and 11 year old 6 th grade students in this study tended to report the highest levels of uncertain c ontrol. In summary, b ased on the findings of this study, the following conclusions were drawn. 1) M iddle school agricultural education students in this study tended to report higher adaptive motivational thoughts than adaptive engagement behaviors and tend ed to report higher maladaptive motivational thoughts than maladaptive engagem ent behaviors More specifically, 12 year old 6 th grade females in the study tended to report the highest motivational thoughts and 14 year old and 7 th grade students in the stu dy tended to report the highest scores of m aladaptive motivational thoughts. 2) Within the individual constructs of adaptive motivational thoughts students in this study tended to report higher scores in the construct learning focus and the lowest scores in the construct valuing. Specifically, female students in the study tended to report higher scores in self belief, valuing, and learning focus than male students Furthermore, the highest levels of self belief and learning focus we re seen in 7 th grade stude nts with in the study However, the levels of self belief we re higher than learning focus at 12 and 14 years old in this study and valuing wa s most important for sixth grade students of th e study 3) Within the individual constructs of maladap tive motivationa l thoughts, students in this study tended to report the highest scores in the construct a nxiety and the l owest scores in the construct uncertain control. More specifically female students in the study tended to report higher maladaptive motivational thoug hts than males. S tudents in the study tended to report the highest levels of a nxiety at 14 years old.

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113 Furthermore 7 th grade and 14 year old students in the study tended to report the highest levels of failure avoidance, and 11 year old 6 th grade students in the study tended to report the highest levels of uncertain control. Objective Two The aim of objective two was to identify self reported perceptions of engagement in middle school agricultural education students. Martin (2012) indicated that higher sc ores on adaptive engagement behaviors (persistence, task management, and planning) were considered better than lower scores. M iddle school agricultural education students in this study tended to report lower global booster engagement behaviors (persistence task management, and planning) than global booster thoughts. Particularly, 12 year old 6 th grade females in this study tended to report the highest global booster engagement behavior s. Separating the constructs which comprise global booster engagement be havior s it was concluded that middle school agricultural education students in this study tended to report higher scores in the construct task management and the lowest scores in the construct planning. However, 14 year old students in this study tended to report higher levels of persistence than task management. Moreover, 7 th grade students in this study tended to report the highest levels of task management and planning, while 6 th grade students in this study tended to report the highest levels of persist ence. Additionally, Martin (2012) noted that lower scores on maladaptive engagement behaviors (disengagement and self sabotage) were considered better than higher scores. Middle school agricultural education students within this study tended to report low er global guzzler engagement behaviors (self sabotage and disengagement) than muffler thoughts. In particular, 14 year old 8 th grade males within this study tended to report the highest global guzzler engagement behaviors.

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114 Distinguish ing between the const ructs of global guzzler behaviors middle school agricultural education students in this study tended to report higher levels of self sabotage than disengagement Specifically, 14 year old 8 th grade males in the study tended to report the highest levels of self sabotage. However, 11 and 12 year old students in the study tended to report higher levels of disengagement than self sabotage In summary, based on the findings of this study the following conclusions were drawn. 1) Middle school agricultural educati on students in this study tended to report lower scores of adaptive engagement behavior s than adaptive motivational thoughts, and tended to report higher scores of maladaptive engagement behaviors than maladaptive motivational thoughts. More specifically, 12 year old 6 th grade females in the study tended to report higher levels of adaptive engagement behavior s, and 14 year old 8 th grade students in the study tended to report higher levels of maladaptive engagement behaviors 2) Within the constructs of adapti ve engagement behavior s middle school agricultural education students in this study tended to report higher scores in the construct task management and the lowest scores in the construct planning. The highest levels of task management and planning we re see n in 7 th grade students in the study while the highest levels of persistence we re seen in 6 th grade students in the study 3) Within the constructs of maladapt ive engagement behavior s middle school agricultural education students in the study tended to repo rt higher levels of self sabotage than disengagement The highest levels of self sabotage wer e seen in 14 year old 8 th grade males in the study However, disengagement levels we re higher than levels of self sa botage for 11 and 12 year old students in the s tudy Objective Three The aim of objective three was to examine the relationships between middle grade level) and their perceptions of motivation to learn and engagement in learning.

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115 Findings showed that middle school agricultural education students in higher grade levels in this study tended to report slightly lower global booster thoughts (self belief, valuing, and learning focus) and slightly higher levels of global g uzzler engagement behaviors (self sabotage and disengagement). O lder students within the study tended to report slightly higher levels of global guzzler engagement behaviors and slightly higher muffler thoughts (anxiety, failure avoidance, and uncertain con trol) M ales in the study tended to report slightly higher global guzzler engagement behavior s while females tended to report slightly higher muffler thoughts. In particular, the students in higher grade levels within this study tended to report slightly lower levels of self belief, uncertain control, task management, valuing, and persistence. Additionally, students in higher grade levels within the study tended to report slightly higher levels of self sabotage and disengagement O lder students in the stud y tended to report slightly higher levels of self sabotage and uncertain control. Female students in the study tended to report slightly high er levels of anxiety and learning focus and males within the study tended to report slightly high er levels of dise ngagement. In summary, based on the participants in this study the following conclusions were drawn. 1) M iddle school agricultural education students in higher grade levels within this study tended to report slightly decreased levels of global booster tho ughts and slightly increased levels of global guzzler engagement behaviors Specifically, students in higher grade levels in the study reported slightly decreased levels of self belief, uncertain control, task management, valuing, and persistence, and slig htly increased levels of self sabotage and disengagement 2) Older m iddle school agricultural education students in the study tended to report slightly increased levels of global guzzler engagement behavior s and global muffler thoughts Specifically, older s tudents in the study tended to report slightly increased levels of self sabotag e and uncertain control

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116 3) Male m iddle school agricultural education in this study tended to report slightly higher levels of global guzzler behaviors and females in the study t ended to report slightly higher levels of global muffler thoughts. More specifically, f emale agricultural education students in this study tended to report slightly high er levels of anxiety and learning focus, while males within the study tended to report slightly high er levels of disengagement. Discussion and Implications Objective One reported perceptions of motivation to learn. Conclusion 1 : Middle school agricultural education students in t his study tended to report higher adaptive motivational thoughts than adaptive engagement behaviors, and tended to report higher maladaptive motivational thoughts than maladaptive engagement behaviors. More specifically, 12 year old 6th grade females in th e study tended to report the highest motivational thoughts, and 14 year old and 7th grade students in the study tended to report the highest scores of maladaptive motivational thoughts. The expectation of the researcher was that participants in this study would report fairly high amounts of motivation to learn due to nature of self reporting data collection. Additionally, earliest theories of motivation states that people are inherently determined to uphold an optimal level of excitement because it is phys iologically pleasing (McLaughin et al., 2005). It can also be assumed that the high levels of motivation to learn can be accredited to the combination of the classroom, SAE, and FFA activities which make up an agricultural education program According to H ughes and Barrick (1993), FFA activities and SAEs serve as reinforcement tools and motivation by recognizing students for exemplary performance. Ryan and Patrick (2001) noted that young adolescence marks the beginning in a d ownward movement in academics. The 6 th grade is the first grade to enter middle

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117 school. It can be assumed that motivation to learn is at its peak during this stage because students are excited to be entering new school and classroom environments. Additionally, it can be assumed that the peak of motivation occurs at 12 years of age because between 11 and 12 years of age students began to face emotional and operational intelligence and formal operational intelligence (Fisher, 2005; Salkind, 2008). T he reporting of girls having more adaptive motivational thoughts are consistent with the literature which states that females are more motivated and engaged in academics (Marks, 2000). Additionally, Ryan and Pa trick (2001) also noted that middle school aged children start to become uncertain in their abilities to succeed in school. This is consistent with the findings of this study that 14 year old and 7 th grade students tended to report the highest levels of ma ladaptive motivational thoughts. After 6 th grade stages and students begi n to become uncertain in their a bilities to succeed in school. Conclusion 2 : Within the individual c onstructs of adaptive motivational thoughts, students in this study tended to report higher scores in the construct learning focus and the lowest scores in the construct valuing. Specifically, female students in the study tended to report higher scores in self belief, valuing, and learning focus than male students. Furthermore, the highest levels of self belief and learning focus were seen in 7th grade students within the study. However, the levels of self belief were higher than learning focus at 12 and 14 years old in this study, and valuing was most important for sixth grade students of the study.

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118 The conclusion was d rawn that participants tended to report high er levels of d gain satisfaction in mastering what they have set out to do (Martin, 2012). These findings are consistent with self determination theory claims of competence in which humans have a need to control desired outcomes and feel successful in brining the desi red outcomes to life (Dolezel, 2011). Additionally, the conclusion was drawn that students within the study tended to report lower scores in the motivational construct of valuing. Value refers to the motives and enticements students view for participating in learning, interesting in activities, importance of the activity to the individual and apparent worth of the activity (Wigfield & learning tasks (McLaughlin et al., 2005). These findings were consistent with Ryan and abilities to succeed in school and begin to question the value of completing school work. The notation that students in th is study tended to report lower levels of valuing i s important in addressing the high school dropout crisis facing the U.S. school system Recommendations to the educators who participated in this study will include ways to increase their student s value o f schoolwork as a method of intervention to address the high school dropout crisis. As Fredricks et al. (2004) noted levels have been attributed to low student motivat ion and engagement in learning, and low achievement levels l ea d to eventual student dropout behavior. Conclusion 3 : Within the individual constructs of maladaptive motivational thoughts, stud ents in this study tended to report the highest scores in the construct

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119 anxiety and the lowest scores in the construct uncert ain control. More specifically, female students in the study tended to report higher maladaptive motivational thoughts than mal es. Students in the study tended to report the highest levels of anxiety at 14 years old. Furthermore, 7th grade and 14 year old students in the study tended to report the highest levels of failure avoidance, and 11 year old 6th grade students in the study tended to report the highest levels of uncertain control It was also concluded th e middle school agricultural education students in this study tended to report high levels of a nxiety. According to need achievement and self worth motivation theory the students in this study could be classified as failure avoidant students. Failure avoidant students tend to be anxious and are motivat ed by fear of failure, often live in self doubt, and are uncertain about their ability to avoid failure and achieve success (Martin, 2012). The assumption could be made tha t middle school students within this study are prone to suffering from anxiety becaus e they are entering their own identity and definition of self through defining an interest in career choices, furthering education, and trade skills (Lee, 2005). Accordi ng to Martin (2012) failure avoidant students may actively self sabotage or handicap their chances of success due to their anxiety. The conclusion that females within the study tended to report higher levels of maladaptive motivational thoughts is consist are consistently more engaged in academics than males. It can be assumed that if females are more prone to being successful in school their levels of anxiety, failure

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120 avoidance, and uncertain control are going t o increase due to their desire to be successful. The assumption can be made that 14 year olds tended to report the highest levels of anxie ty in this study due to the approaching transition from middle school to high school. The anxiety of an approaching t ransition between schools can lead to uncertainties about their abilities to be successful w hich can be linked to the conclusion that 14 year old students in this study tended to report the highest level of failure avoidance. Additionally, it was conclud ed that seventh grade students within the study tended to report h igh levels of failure avoidance. The assumption can be made that seventh grade students tend to report higher levels of failure avoidance due to their uncertainty in their abilities to be su ccessful in school which can be attributed to the cognitive changes occurring as they transition development. Finally, the conclusion that 11 year old 6 th grade students within this study tended to report t he highest levels of uncertain control can be attributed to the challenges of adjusting to new school and classroom environments. perceptions of high levels of anxiety is another essential component in addressing the high school dropout crisis in the US. Recommendations to educators who participated in this study will include methods to reduc e anxiety within the ir classroom as a means of intervention to the high school dropout crisis. Providing these educators with the ability to reduce their student anxiety levels can help to increase their student motivation and engagement, and in turn begin to address low

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121 levels of student achievement within their schools which can lead to student dropout behavior. Objective Two Identify reported perceptions of engagement in learning. Conclusion 1 : Middle school agricultural education students in this study tended to report lower scores of adaptive engagement behaviors than adaptive moti vational thoughts, and tended to report higher scores of maladaptive engagement behaviors than maladaptive motivational thoughts. More specifically, 12 year old 6th grade females in the study tended to report higher levels of adaptive engagement behaviors, and 14 year old 8th grade students within the study tended to report higher levels of maladaptive engagement behaviors. The expectations of the researcher were that participants would report lower adaptive/maladaptive b ehaviors due to the nature of self reporting data collection. Due to human nature students are going to naturally be inclined to have higher motivational thoughts (McLaughin et al., 2005). H owever, engagement behaviors (planning, task management, persist ence) stem from facilitations and reinforcements from adult figures. Additionally, the lack of having adaptive engagement behaviors for the students in this study led way to being more affected by maladaptive motivational thoughts (anxiety, uncertain contr ol, and failure avoidance) than engagement behaviors (self sabotage and disengagement). This is consistent with the conclusions that the middle school agricultural education students in this study tended to report lower adaptive engagement behaviors and lo wer maladaptive engagement behaviors than maladaptive motivational thoughts.

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122 The conclusions that 12 year old 6 th grade female students in this study tended to report higher levels of adaptive engagement behaviors are consistent with Marks (2000) in that females are more academically engaged with boys, and the conclusions from objective one in that 6 th grade is the first grade of middle school in which students have not yet begun to face the emotional and cognitive challenges associated with biological tr ansitions. Finally, the conclusion in that 14 year old 8 th grade students in this study tended to report higher levels of maladaptive engagement behaviors is consistent with perception of competence and subjective value decline as children grow older. Conclusion 2 : Within the constructs of adaptive engagement behaviors middle school agricultural education students in this study tende d to report higher scores in the construct task management and the lowest scores in the construct planning. The highest levels of task management and planning were seen in 7th grade students in the study, while the highest levels of persistence were seen i n 6th grade students in the study. The conclusion was drawn that when self reporting engagement in learning, students in this study tended to report higher scores in the construct task management. These findings are consent with students reporting high sc ores in learning focus as both constructs are a component of self determin ation theory and h umans have a need to control their desired outcomes in order to feel successful (Dolezel, 2011). It can be assumed that the hi ghest levels of task management were r eported by 7 th grade

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123 students in this study because these studies are more adjust ed to transitions in schooling and teacher expectations that 6 th grade students. Additionally, the conclusion was drawn that students in this study tended to report the lowes t scores in the adaptive engagement construct of planning. While this construct is also a component of self determination theory the assumption can be made linked to the conclusion that students tended to report the lowest scores in self sabotage. T he assumption can be made that the highest reported level s of planning were seen in 7 th grade students in this study because 7 th grade aged students are typically age in which students begin to mark their identity by describing interest in career choices and further education. Finally, the assumption can be made that th e highest level of persistence were seen in 6 th grade students within this study because 6 th grad e marks the beginning of middle school While 6 th grade students in the study tended to report the highest levels of adaptive motivational thoughts, t ypically 6 th grade students are faced wi th the struggles of transitioning to new sch ool and classroom envi ronments, thus increasing their levels of persistence. perceptions of low levels of planning is another essential component in addressing the high school dropout crisis in the US. Recommendations to educators who participated in this study wil l include methods to increas e planning for their students as a means of intervention to the high school dropout crisis. Providing those educators who participated in this study with the ability to assist their students in increasing their le vels of planning will help to increase their student

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124 within the classroom, and in turn begin to address low levels of student achievement which can lead to student dropout behavior. Conclusion 3 : Within the const ructs of maladaptive e ngagement behaviors middle school agri cultural education students in the study tended to report higher levels of self sabotage than disengagement. The highest levels of self sabotage were seen in 14 year old 8th grade males in the study. However, disengage ment levels were higher than levels of self sabotage for 11 and 12 year old students in the study. According to Martin (2012) failure avoidant students can actively sabotage their chances of success (ie. procrastinating or lack of planning) in order to pro vide an excuse for their lack of perform ance T his excuse is used a s a protective measure for to attribute their poor performance to their lack of planning rather than a possible lack of ability (Martin, 2012). This stems from conclu sions drawn i n objective one that the middle school agricultural education students in this study reported high levels of anxiety. Their anxiety increases their levels of uncertain control and in order to become failure avoidant students begin to self sabotage themsel ves in order to protect their egos. The conclusions that the highest level of self sabotage were seen in 14 year old males within this study is consistent with the findings of this study that older stude nts, particularly male students tended to report the highest levels of anxiety and failure avoidance. perceptions of high levels of self sabotage is another essential component in addressing the high school dropout crisis in the US. Recommendations to educators that participated i n this study will include methods to de creasing the tendency for students to self sabotage as a means of intervention to the

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125 high school dropout crisis. Providing the educators who participated in this study with the ability to assist students in de creasin g their sabotage will help increase their student engagement, and in turn begin to address low levels of student achievement which can lead to student dropout behavior within their school Objective Three Examine the relationships between middle school agricultural education studen ( a g e g e n d e r a n d g r a d e l e v e l ) and their perceptions of motivation to learn and engagement in learning. Conclusion 1 : Middle school agricultural education stud ents in hi gher grade levels in this study tended to report slightly decreased levels of global booster thoughts and slightly increased levels of global guzzler engagement behaviors. Specifically, stud ents in higher grade levels in the study reported slightly decreas ed levels of self belief, uncertain control, task management, valuing, and persistence, and slightly increased levels of self sabotage and disengagement. The expectations of the researcher were that as grade level increased motivation and engagement would decrease. The conclusion was drawn that students in higher grade levels within this study tended to report slightly lower levels of self belief, uncertain control, task management, valuing, and persistence. These findings are findings that engagement in academic work decreases as grade level increases. The assumption can be made that this is due to the increase changes in domain specific task values in higher grade levels (Martin, 2007). Students in higher grade levels in this study also tended to report slightly higher levels of self sabotage and disengagement. According to Martin (2012) students can result to self sabotaging themselves and becoming disengaged due to their anxiety to be successful. The assumption can be made t hat as students progress into highe r grade levels they are more prone to self sabotage and disengagement due to the

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126 operational intelligence (Fisher, 2005; Salkind, 2008). Add itionally, it can be assumed that students may become disengaged due to the lack of understanding content. These assumptions and conclusions are consistent with the conclusion that older students within this study tended to report slightly higher levels of self sabotage and uncertain control as older students are typically found in higher grade levels and biologically are undergoing the transformation between cognitive stages. The relationships identified in the results of this study also provide key insig hts in addressing the high school dropout crisis facing the US. Recommendations on ways to address the constructs in which students identified least with will be made to those educators who participated in this study The low relationship identified in thi s objective is important to note to those agricultural educators wh o participated in this study This relationship demonstrates to those educators that there is a need to focus on improving self belief, uncertain control, task management, valuing, and pers istence for students in higher grade levels levels of self sabotage and disengagement. Focusing on their higher grade level students in th ese construct areas can help improve student motivation a nd engagement in learning and in turn help to lowe r the rate of student dropouts within those schools. Conclusion 2 : Older middle school agric ultural education students i n the study tend ed to report slightly increased levels of global guzzler engagement behaviors and global muffler thoughts. Specifically, older students with the study tended to report slightly increased levels of self sabotage and uncertain control.

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127 The expectations of t he researcher were that as age increased motivation and findings that upper elementary students (ages 9 11.5) reflect higher levels of motivation there is a decline in motivation between elementary and middle school. Older s tudents in this study also tended to report slightly higher levels of self sabotage and uncertain control According to Martin (2012) students can result to self sabotaging them selves and becoming disengaged due to their anxiety to be successful. Students who are transitioning through this cognitive developmental stage may have yet to develop the cognitive structures of understanding (Salkind, 2008) and therefore are suffer from self sabotaging their school work in order to protect themselves from feeling a lack of intelligence. The relationships identified in the results of this study also provide key insights in addressing the high school dropout crisis facing the US. Recommenda tions on ways to address the constructs in which students identified least with will be made to those educators who participated in this study The low relationship identified in this objective is important to note to the educators that participated in thi s study T his relationship demonstrates to those educators that there is a need to focus on improving self sabotage and uncertain control for older students within their classrooms Focusing on the older middle school students within their classrooms for t hese construct areas can help improve student motivation and engagement in learning in the agricultural education programs which participated in this study and in turn help to lower the rate of student dropouts within those schools

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128 Conclusion 3 : Male m iddle sc hool agricultural education in this study tended to report slightly higher levels of global guz zler behaviors, and females in the study tended to report slightly higher levels of global muffler thoughts. More specifically, female agricultural educa tion students in this study tended to report slightly higher levels of anxiety and learning focus, while males within the study tended to report slightly higher levels of disengagement. In regards to their self perceptions of motivation and engagement in learning, m ales within this study tended to report slightly higher levels of disengagement in this noted to consistently be less engaged in academics than females. The ass umption can school, view of homework as less useful, and unwillingness to ask for help or complete ex tra school work (Martin, 2007). Additionally, in regards to their self perceptions of motivation and engagement in learning, f emales within this study tended to report slightly higher levels of anxiety and females are higher achieving than m ales and more females were noted to complete school than males since 1976. The assu higher levels of anxiety could be due to their need to perform better in school than males. The relationships identified in the results of this study provide key insights in addressing the high school dropout crisis facing the US. Recommendations on ways to address the constructs in which students identified with least will be made to those educators who participated in this study The low re lationship identified in this objective

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129 is important to note to those educators. The relationship found in this study demonstrates to the educators who participated in this study that there is a need to focus on decreasing disengagement levels for males a nd decreasing anxiety levels for females Focusing on these construct areas within males and females can help improve student motivation and engagement in learning for the students within this study, and in turn could help to lower the rate of student drop outs within those schools which participated in this study. Recommendation for Practitioners Based on the findings of this study, the following recommendations were made for the educators who participated in this study : 1) Students in this study tended to r eport lower levels of valuing. The following examples are methods for the educators who participated in this study to improve e in their schoolwork. a. E ducators should make connections between curriculum and world events (Martin, 2012). F or instance providing students with the opportunity to work with genuine problems or community based problems allows students to see how their school work is relevant in their lives, s uch as incorporating research on a drought affecting the community into an environmental unit. b. Educators should also make connections to curriculum being taught in other subjects (Martin, 2012). Connecting curriculum taught in their agricultural education classes to math, science, and reading concepts demonstrates to students the consecutiveness of all subjects taught within a school environment. Educators who participated in this study should work on teams with other subject area teachers to accomplish this recommendation. For example, the water cycle being taught in a scienc e course could be related to a horticulture, environmental, and/or soil science unit being taught in the agricultural classroom. c. Educators should also encourage students to think critically and analyze ways curriculum can be helpful in their individual li ves (Martin, 2012) E ncouraging students to think critically and analyze ways curriculum is relevant to their individual lives provides students the connection of lessons learned in the classroom to their social and personal lives which can be transferred later in to their careers. Educators can provide

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130 opportunities for critical thinking and analyzing by developing activities which allow students to explore lesson concepts in their lives. For example, providing an activity which requires students to track their opportunities for critical thinking and analyzing food science concepts in daily lives. d. E ducators should serve as role models by showing value towards curriculum being taught (Martin, 2012) It is important for the educators in this study to show enthusiasm in their teaching. Demonstrating their own value towards the curriculum helps display the importance of curriculum to students. These recommendations can aid the educators who participated in this study in alu e towards their schoolwork as valuing has been described as the extent to which students believe what they learn in school is useful and relevant to them (Martin, 2012) 2) Students in this stu dy tended to report high levels of anxiety. The following are recommendations to educators who participated in this study to help reduce anxiety within their classrooms. a. To reduce anxiety educators in this study should reduce uncertainty in the classroom by communicating clear expectations and objectives (Martin, 2012) When educators communicate to their students their expectations for behavior and in academics students levels of anxiety are lowered. Educators who participated in this study can communicat e clear expectations by first reviewing expectations at the beginning of the school year, and then educators should strive to be consistent with these expectations throughout the school year. Educators can also be clear about expectations and objectives by providing rubrics for class assignments and projects. Additionally, e ducators should display their expectations within the classroom and should display daily objectives and schedule s in a visible area for students. b. Educators can also help students reduce anxiety leading up to assessments by teaching review techniques and clearly explaining material to be covered on the test (Martin, 2012) Today students are faced with an abundance of testing, and each teacher a student encounters may have a different tes ting style s The educators in this study should teach their students ways to review for their tests, whether that is using vocabulary flash cards or outlining techniques for notes or chapters in the text book In addition to review techniques educators s hould clear ly explain which material will be covered on assessments, f or example pr oviding reviews in class and study guides that include important concepts which will be included on assessments.

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131 c. Educators can also teach students how to recognize the sign s of anxiety (Martin, 2012). Helping students recognize the feelings of nervousness, feeling sick to their stomachs, and racing heart beat s are signs of anxiety can help students to learn ways to relax, f or instance teaching students to practice deep brea thing or focusing on answering the question rather than thinking about if they will fail (Martin, 2012). These recommendations for educators who participated in this study can help in reducing studen t anxiety within the classroom as a nxiety ha s been descr ibed as a twofold construct in which students suffer from feeling nervous and worrying (Martin, 2012) 3) Students in this study tended to report lower levels of planning. The following are recommendations to educators who participated in this study to help increase a. To improve student planning educators should ensure students have clear understandings of expectations on assignments and test s (Martin, 2012) Providing students with clea r expectations on assignments and test s will enable st udents the ability to plan their work on assignments and study habits for test s Educators in this study can provide clear expectations on assignments by providing example work and a grading rubric to students, and clear expectations on tests can be provid ed through reviews and study guides/packets. Educators can also help students plan for assignments and test by clearly explaining to students the meaning of key words that will be included in directions, such as compare, analyze, summarize, and discuss (Ma rtin, 2012). b. Educators can also help students plan by demonstrating how to check student progress and devel op strategies for checking work as it is completed (Martin, 2012). Educators in this study can show students how to check electronic grade books (fo r schools which provide these) to check their grades and missing assignments Educators can also provide specific procedures for students to check for missed work when absent. Finally, educators in this study can teach stu dents strategies to check the prog ress of their work as it is co mplete d through demonstrating how to ask clarifying questions and how to check work using notes and chapters in the textbook. c. Educators can demonstrate better planning by showing how to break school work into components by ou tlining and think ing about assignments (Martin, 2012) When assigning extended projects or projects which contain a great deal of detail educators can provide multiple checks during the duration of the project to demonstrate to students how to break apart the assignment and complete their work in portions.

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132 d. Educators can show students how to use time more effectively by priori tizing work (Martin, 2012). Educators in this study can demonstrate to students how to record due dates in their student planner. Th is will help students visualize when assignments are due and prioritize those which are most pressing to be completed first. These recommendations to the educators who participated in this study will help students within their classroom develop planning sk ills as p lanning refers to how much students plan their assignments and homework and how much they keep tr ack of progress in school work (Martin, 2012). 4) Students in this study tended to report high levels of self sabotage. The following are recommendations to educators who participated in this study to help reduce sabotage. a. To reduce self sabotage educators should make it clear to students that their worth is not determined by their grades but rather their effort (Martin, 2012) It is important for educators to teach the notation of hard work and effort. This will help students to understand that their hard work and effort has more value than their actual grade. b. Educators can also show students their mistakes and ways to impro ve them (Martin, 2012). Educators in this study should dictate the message to their students that mistakes show students where they went wrong and helps to point out areas in which students need to improve upon (Martin, 2012). Educators should demonstrate to students to be optimistic, and that (Martin, 2012 p.69 ) c. Educators can also have students reflect on times they have self sabotaged (Martin, 2012) Educators can help students reflect on times in which they have self sabotaged by asking students to make lists of subjects in which they have self sabotaged and to have them think about how they feel abo ut those subject areas. This will enable educators to pin point the underlying reasons for their self sabotag e, whether that be actual learning focus, anxiety, uncertain control, failure avoidance, etc. (Martin, 2012). These recommendations will aid the teachers in this study in reducing their elf sabotage as self sabotage is when students do things to reduce their success in school like putting of f assignments or wasting time (Martin, 2012) 5) Older students and students in higher grade levels within this study tended to report lower levels of self belief, uncertain control, task manageme nt, a nd persistence, as well as higher levels of disengagement. The following are recommendations to educators who participated in this study on ways to improve these constructs.

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133 a. Older s tudents and students in higher grade levels with in this study tended to re port lower levels of self belief. Recommendations to educators on ways to increase student self belief are as follows: i. Educators can improve student self belief by maximizing opportuniti es for success in the classroom (Martin, 2012). For instance, breakin g assignments into smaller components which enable students to experience smaller successes along the way (Martin, 2012) s uch as, providing worksheet s practice assignments for objectives, and activities to practice new vocabulary. ii. Educators can also hel p students to rework their definition of success into one that is accessible by all students (Martin, 2012). capabilities (Martin, 2012) e (Individualize d Education Plans). iii. Educators who participated in this study need to communicate positive expectations to their students (Martin, 2012). Communicating positive expectations to students provides them with higher thought s of themselves and helps them to rec ognize improvements they can make in their schoolwork. iv. Educators can also help students to identify and challenge their negative self beliefs about themselves and school work (Martin, 2012) Educators can do this by having students identify and reflect ch allenges they have experience in their school work, and think about ways in which they can improve upon those challenges. These recommendations will aid educators in this study in increasing their belief as s elf belief i s students confidence in their own ability to understand or do well in school work ( Martin, 2012) b. Older s tudents and students in higher grade levels with in this study tended to report high levels of uncertain control. The following are recommendations to educators who participated in this study to decrease i. Educators can reduce uncertain control in students by showing them how to recognize the aspect of school work in which they can control (Martin, 2012). Edu cators who participated in this study should focus on explaining to students that they have control over their own effort they put into their schoolwork, the strategies they use to complete their schoolwork, and the attitude they have towards themselves, t heir teachers, and their schoolwork (Martin,

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134 2012). The school work are what enable them to be successful in the classroom. ii. On the same note, educators who participated in this study must encourage stu dents not to focus on aspec ts in which they cannot control (Martin, 2012). Educators need to clearly communicate to students to recognize that they can not control aspects of their schoolwork such as the difficulty of an assignment or distracters in the cla ssroom (Martin, 2012) As a result, educators need to express to students to not focus on the aspect in which they cannot control but rather those in which they can control in order to be successful in the classroom. iii. Educators should also giv e feedback on student work to help Educators can accomplish providing effective feedback to their students by providing task based feedback, in that educators should explain to students what aspects of the ass ignment students can improve upon (Martin, 2012). For example, educators can make notes on assignments for students to practice vocabulary words to better be able to ex plain concepts within the unit, or to focus on a specific step within the process lesson objective iv. Educators who participated in this study can help reduce levels of uncertain control by helping students develop a sense of control in the classroom (Martin, 2012). For instance, providing choices of achieving lesson objectives or the order in which tasks are completed (Martin, 2012) f or example, allowing students to complete a specific objective before another objective. Additionally, educators can provide students the opportunities to choose specific topics for research (Martin, 2012) such as allowing students to choose a topic to research which interest them that is related to the material. For example, during a horticultural unit a student with an interest in bees could choo se to research how bees affect pollination. These recommendations can aid the educators who participated in this level of uncertain control as u ncertain control doing poorly in school (Martin, 2012) c. Older s tudents and stu dents in higher grade levels with in this study tended to report lower levels of task management. Recommendations to educators who participated in this study on ways to improve student task management are as follows:

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135 i. Educators can help students increase th eir task management by encouraging students to create to do lists (Martin, 2012). Educators should show students how to creative effect to do lists with assignments in all subjects in order to help students stay on task and accomplish assignments. ii. Educato rs should also help students create homework timelines (Martin, 2012) Educators should ask students to reflect on their homework/study time for a week, and record details such as where they complete their homework, who they complete their homework with, a nd what time of the day do they work on their homework, and what conditions do they complete their homework under (Martin, 2012) Educators should then help students analyze those variables which help them to effectively complete their homework and encoura ge students to do their homework under these conditions more often. These recommendations can aid the teachers who participated in this task management skills as t ask management has been described as the way students us e their schoolwork and homework time (Martin, 2012) d. Older s tudents and students in higher grade levels with in this study tended to report lower levels of persistence. The following are recommendations to educators who participat ed in this study to aid in increasing their i. Educators can improve student persistence by teaching students steps to goal setting (Martin, 2012). Educators in this study should use their FFA unit to teach SMART goals, in which students will learn ho w to set goals which are specific, measureable, attainable, realistic, and timely. As a part of the SMART goals lesson e ducators should have students create SMART goals for their agricultural education assignments which will in turn encourage students to be persistent in their school work. ii. Educators in this study can also hav e their students reflect on ways to overcome difficulties in schoolwork (Martin, 2012) Educators should encourage students to consider ways they get in the way of their own successes (for instance self sabotage) and ways to prevent those feelings in the future. Educators should also encourage students to reflect on their efforts and to recognize that effort leads to improvement and successes (Martin, 2012). These recommendations can aid the educators in this study in increasing their students levels of persistence as p ersistence refers to how much

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136 students continue to try understanding difficult or challenging problems in school work (Martin, 2012) e. Older students and students in h igher grade levels with in this study tended to report high levels of disengagement. The following are recommendations to educators who participated in this study as methods i. Educators can help reduce stu dent disengagement by encouraging students to understand they are not helpless and they control their own quality of schoolwork, who they wo rk with, and what they work on (Martin, 2012). It is important for educators who participated in this study to commu nicate these notations with their students. By communicating these notations with students, students may identify the educator as a person who will support them as they become more engaged in school work (Martin, 2012). ii. Educators can also decrease disenga gement by increasing stude nt interaction in the classroom (Martin, 2012). Increasing student interaction provides opportunities for social interaction and increase s in this study should provide activi ties which allow cooperative group work, f or example, setting up labs in which students are assigned groups or partners. iii. Educators who participated in this study can also reduce disengagement levels by providing opportunity for students to explo re curric ulum in the classroom (Martin, 2012). Providing opportunities for students to explore curriculum aids in demonstrating the relevancy of curriculum to students. Educators can provide opportunities to explore curriculum through providing interaction with peo ple beyond the environment of the classroom and school (Willms et. al, 2009), such as inviting guest speakers which correlate with the lessons bei ng taught within the curriculum. Additionally, e ducators can also provide multimedia instruction (Deleavy & Mi lton, 2009), such as using the internet to research issues within the curriculum or to Skype with experts around the world. Educators can also us e multimedia items such as cameras, videos, smart boards, and PowerPoint for assignments to allow students oppo rtunities for creativity (Deleavy & Milton, 2009) The following recommendations can aid the educators who participated in levels of disengagement as d (Martin, 2012)

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137 Recommendations for Further Research Based upon the findings of this study, the following recommendations for further researchers were made : 1) To replicate this study using procedures which allow for randomization of a sample of students in order t o provide more generalizability as this research design used a convenience sample of students from the classrooms of those agricultural educators who agreed to participate in the study. 2) F urther studies should be conducted which investigate the v ariables of student motivation and engagement which extend beyond student self perceptions of motivation and engagement as used in this study, in order to prevent the possibility of socially desirable answers, a lthough the assumption in this study was tha t students responded in a truthful manner. 3) F urther studies should investigate the impact of environmental attributes (home influences, peer pressures, societal norms, and institutional influences) on g as this study focused motivation to learn and engagement in learning. 4) Further research should be conducted in the form of an experimental study to investigate the impact of in terventions recommended to educators, as a result of this study on student motivation and engagement

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138 APPENDIX A INVITATION TO TEACHE RS September 1 2012 Dear Agricultural Educator, I am a University of Florida Graduate student conducting a studyi ng on motivation and engagement in middle school agricultural education students I am collect ing data from agricultural education middle school students in North Central Florida on their perceived motivation and engagement in the classroom. I have indicat ed you as a middle school agricultural educator in North Central Florida and am requesting your assistance by allowing me to collect data from your students. Students will complete a short Motivation and Engagement questionnaire which will be sent to parti cipating teachers in the beginning of November and should take 10 15 minutes for students to complete. My goal is to s hare d engagement with middle school agricultural education teachers at the completion of th e study I hope that you will be able to assist me in collecting this valuable information from students in order to shed light into how we as educators can continue to improve our teaching strategies to increase student motivation and engagement in the cl assroom. I will be in contact with you by phone soon to answer any questions you may have about the procedures of this study. I thank you for your time and assistance i n collecting data for this study. Please feel free to contact me if you have any quest ions at ashcrffa@ufl.edu Sincerely, Ashley Young Ashley Young Graduate Student Agricultural Education and Communication University of Florida

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139 APPENDIX B MOTIVATION AND ENGAGMENT SCALE Adapted from ( Life long Achievement Group, 2012) Dear Student, Welcome to the Motivation and Engagement Scale. This survey has been given to you to find out your motivation and engagement towards schoolwork and how you think of yourself as a student. There are no right or wrong answers. Make sure to read the questions completely and try your best to give an honest answer. Your name will not be connected to this survey in any way and your teacher will not know your answers. You should have one answer for each question. It is best to answer every question, if you are unsure of an answer circle the one that is closest to what you think. If you have any concerns please talk to your teacher who gave you the survey. There are some questions that are similar to each other. Thi s is not to trick you. To get the best judgment of your motivation and engagement this survey needs to ask similar questions in different ways. Remember to answer in a way that shows what you really think about yourself. Here is an example: Disagree St rongly Disagree Neither Agree or Disagree Agree Agree Strongly 1 2 3 4 5 Strongly Disagree Agree Strongly I work hard at school 1 2 3 4 5 Ask your teachers if you have any questions. You may now begin. School : ______________________ Age: ______________________ Grade: (Please circle one) 6 th Grade 7 th Grade 8 th Grade Gender: (Please circle one) Male Female

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140 Due to copyright license agreements the complete MES JS instrument could not be included in the appendices. The ins trument was a 44 item questionnaire comprised of four items for each of the eleven factors (Martin, 2012). The questionnaire was a 5 point Likert type scale with answer choices consisting of 1 ( Strongly Disagree ) to 5 ( Strongly Agree ) (Martin, 2012). Copy right agreements allow for one sample item per each of the 11 sub scales to be included. They are as follows: 1) Self Belief 2) Valuing 3) Learning Focus 4) Planning plan 5) Task Management 6) Persistence 7) Anxiety 8) Failure Avoidance 9) Uncertain Control 10) Self sabotage 11) Disengagement

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141 APPENDIX C ADMINISTRATION PROTOCO L Dear Agricultural Educator engagement in the classroom will help in shedding light into how middle school agricultural education students are motivat ed and engaged. Upon completion of this study you will receive information In your packet you will find the following documents. 1. Informed Parental Cons ent Form & Informed Student Consent Form 2. Motivation and Engagement JS Survey 3. Survey Administration Directions 4. Empty Manila Envelope Please distribute the Informed Parental Consent & Informed Student Consent forms to your students. After you have collected these consent forms you may administer the Motivation and Engagement JS Survey Please only administer the survey to those students who have turned in the Informed Parental Consent and Informed Student Consent Form. Please make sure that your students u nderstand that their survey is completely anonymous. Also, please make it clear that you will not see their responses to the questions as they will place their completed survey in the empty manila envelope upon completion. Please make it clear that student s should answer the questions honestly. When administering the survey please read the directions on the front page of the survey ( Survey Administration Directions ) aloud to your students and answer any questions to the best of your ability. Make sure to tell students not to write their names on their survey. After they have completed their survey instruct them to place their survey in the manila envelope. This survey should take 10 15 minutes to complete. Once you have collected all completed surveys pl ease return them with any blank surveys you may have by December 31 st 2012 to: Dr. Kirby Barrick C/O Ashley Young P.O. Box 110540 University of Florida Gainesville, Fl 32611 Again, thank you for your time and cooperation with this study. Sincerely A shley Young Graduate Student University of Florida

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142 After distributing the Motivation and Engagement Scale JS to your students, please read these directions aloud and have your students follow along. Motivation and Engagement Scale JS Dear Stud ent, Welcome to the Motivation and Engagement Scale. This survey has been given to you to find out your motivation and engagement towards schoolwork and how you think of yourself as a student. There are no right or wrong answers. Make sure to read the questions completely and try your best to give an honest answer. Your name will not be connected to this survey in any way and your teacher will not know your answers. You should have one answer for each question. It is best to answer every question, if you are unsure of an answer circle the one that is closest to what you think. If you have any concerns please talk to your teacher who gave you the survey. There are some questions that are similar to each other. This is not to trick you. To get the best judgment of your motivation and engagement this survey needs to ask similar questions in different ways. Remember to answer in a way that shows what you really think about yourself. Here is an example: Disagree Strongly Disagree Neither Agree or Disag ree Agree Agree Strongly 1 2 3 4 5 Strongly Disagree Agree Strongly I work hard at school 1 2 3 4 5 hard all of the hard most of the time. Ask your teachers if you have any questions. You may now begin.

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143 APPENDIX D IRB APPROVAL

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144 APPENDIX E IRB PARENTAL CONSENT

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145 APPENDI X F IRB STUDENT CONSENT

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146 LIST OF REFERENCES Appleton, J. J., Christenson, S.L., Kim, D., & Reschly, A.L. (2006). Measuring cognitive and psychological engagement: Validation of the student engagement instrument. Journal of School Psychology, 44 427 445. Appleton, J. J., Christenson, S.L., & Fulong, M.J. (2008). Student engagement with school: Critical conceptual and methodological issues of the construct. Psychology in the Schools, 45 (5) 369 386. Ary, D., Jacobs, L. C., & Sorenson, C. (2010). Introduct ion to research in education (8 th ed.). Belmont, CA: Wadsworth, Cengage Learning. Balfanz, R., Herzog, L., & Mac Iver, D. J. (2007). Preventing student disengagement and keeping students on the graduation path in urban middle grades schools: Early identif ication and effective interventions. Educational Psychologist, 42 (4), 223 235. Barrick, R. K. (1988). Agricultural education: Building upon our roots. Journal of Agricultural Education, 30 (4), 24 29. doi: 10.5032/jae1989.04024 Barrington, B. L., & Hendri cks, B. (1989). Differentiating characteristics of high school graduates, dropouts, and nongraduates. Journal of Educational Research, 82 (6), 309 319. Carnegie Council on Adolescent Development. 1989. Turning points: Preparing American youth for the 21 st century. Washington, DC: Author. Civic Enterprises Everyone Graduates Center. (2012). Building a grad nation: Progress and challenge in ending the high school dropout epidemic. (Annual Report.) John Hopkins University: Balfanz. R., Bridgeland, J. M., Bru ce, M., & Horning Fox, J. Definitions. (n.d.). In Merriam Webster Dictionary online. Retrieved from http://www.merriam webster.com/dictionary Davis, J. A. (1971). Elementary survey analysis. Englewood, NJ: Prentice Hall. Doerfert, D. L. (Ed.) (2011). Nat ional research agenda: American Association for 2015. Lubbock, TX: Texas Tech University, Department of Agricultural Education and Communications. Dolezal, K. D. (2011). Motivation and engagement: Student and teacher perceptions. (Doctoral Dissertation). Unpublished doctoral dissertation, University of Wyoming. Dunleavy, J. & Milton, P. (2009). What did you do in school today? Exploring the concept of student engagement and its implications for tea ching and learning in Canada. Toronto: Canadian Education Association (CEA), 1 22.

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147 Dunleavy, J., Milton, P. & Crawford, C. (2010). The search for competence in the 21 st century. Quest Journal 2010. Leading Edge Learning.ca (Abstract). Finn, J. D. (1989). Withdrawing from school. Review of Educational Research, 59 (2), 117 142. Fisher, C. B. (2005). Cognitive development. In Encyclopedia of Applied Developmental Science. Retrieved from http://sage ereference.com.lp.hscl.ufl.edu/view/applieddevscience/n101.xml?rskey=59rZ5z&r esult=2&q=piaget's%20theory%20of%20cognitive%20development Fisher, C. B. Encyclopedia of Applied Developmental Science. Retrieved from ht tp://sage ereference.com.lp.hscl.ufl.edu/view/applieddevscience/n101.xml?rskey=59rZ5z&r esult=2&q=piaget's%20theory%20of%20cognitive%20development Fredricks, J. A., Blumenfeld, P.C., & Paris, A.H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74 (1), 59 109. Encyclopedia of Career Development. Retrieved from http://sage ereference.com.lp.hscl.ufl.edu/view/careerdevelopment/n105.xml?result=111&q= Hay, L. R. (2000). Teaching the net generation. Business Education Forms, 54 (3), 6 14. Hughes, M. & Barrick, R. K. (1993). A model for agri cultural education in public schools. Journal of Agricultural Education, 34 (3), 59 67. doi: 10.5032/jae.1993.03059 uninteresting activity. Journal of Educational Psycholo gy, 100 (4), 708 811. Encyclopedia of School Psychology. Retrieved from http://sage ere ference.com.lp.hscl.ufl.edu/view/schoolpsychology/n97.xml?result=99&q= Lee, V. E., & Smith, J. B. (1993). Effects of school restructuring on the achievement and engagement of middle grade students. Sociology of Education, 66 (3), 164 187. Marks, H. M. (2 000). Student engagement in instructional activity: Patterns in the elementary, middle, and high school years. American Educational Research Journal, 37 (1). Retrieved from http://www.jstor.org/stable/1163475 Mac Iver, M. A., & Mac Iver, D. J. (2009). Beyon d the indicators: An integrated school level approach to dropout prevention. Arlington, VA: The Mid Atlantic Equity Center, The George Washington University Center for Equity and Excellence in Education.

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148 Martin, A. J. (2003). The student motivation scale: Further testing of an instrument that Australian Journal of Education, 47 (1), 88 106. Martin, A. J. (2007). Examining a multidimensional model of student motivation and engagement using a construct validation approac h. British Journal of Educational Psychology, 77 413 440. Martin, A. J. (2008). Enhancing student motivation and engagement: The effects of a multidimensional intervention. Contemporary Educational Psychology, 33 (2), 239 269. Martin, A.J. (2009). Motiva tion and engagement across the academic life span: A developmental construct validity study of elementary school, high school, and university/college students. Educational and Psychological Measurement, 69 (5), 794 824. Martin, A.J. (2012). The Motivation and Engagement Scale (12th ed.). Sydney, Australia: Lifelong Achievement Group (www.ligelongachievement.com) McLaughlin, M., McGrath, D. J., Burian Fitzgerald, M. A., Lanahan, L., Scothcmer, M., Enyeart, C., & Salganik, L. (2005). Student content engagemen t as a construct for the measurement of effective classroom instruction and teacher knowledge. Washington, DC: American Institutes for Research. Retrieved from http://www.air.org/files/AERA2005Student_Content_Enagagement11.pdf McMillian, J. H., & Schumach er, S. (2010). Research in education: Evidence based inquiry (7 th ed.). Upper Saddle River, NJ: Pearson. National Center for Education Statistics: Institute for Education Sciences. (2009). Trends in high school dropout and completion rates in the United S tates: 1972 2009 (IES Publication No. 2012 006). Washington, DC: U.S. Department of Education. National Center for Educational Statistics. (2010). Elementary and secondary education. In Digest of Educational Statistics (Chapter 2). Retrieved from http://n ces.ed.gov/programs/digest/d10/index.asp NCLB Act of 2002, Public Law 107 110 115 STAT. 1425 (2002). Newman, F. M. Wehlage, G. G., & Lamborn, S. D.(1992). Student engagement and achievement in American secondary schools. New York, NY: Teachers College P ress. classroom social environment, motivational beliefs, and engagement. Journal of Educational Psychology, 99 (1), 83 98.

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149 Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95, 667 686. Rohs, F. R. & Anderson, K. S. (2001). Motivtional needs of middle grade students enrolled in agricultural education in Georgi a. Journal of Agricultural Education 42 (3), 42 52. Rumberger, R. W. (1987). High school dropouts: A review of issues and evidence. Review of Educational Research, 57 (2), 101 121. Ryan, A. M., & Patrick, H. (2001). The classroom social environment and cha nges in American Educational Research Journal of Educational Psychology, 99 (1), 83 98. Encyclopedia of Educational Psychology (p.798). Retrieved from http://sage ereference.com.lp.hscl.ufl.edu/view/educationalpsycho logy/n215.xml?rskey=vqgm xj&result=1&q=piaget's%20theory%20of%20cognitive%20development Shadish, W. R., Cook, T. D., & Campbell, K. R. (2002). Experimental and quasi experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin. Ski nner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100 (4), 765 781. Skinner, E. A., Kindermann, & T. A., Furrer, C. J. (2009) A motivational perspective on behavioral and emotional participation in academic activities in the classroom. Educational and Psychological Measurement, 69 (3), 493 525. doi:10.11 77/00131644083233 Taylor, L., & Parsons, J. (2011). Improving student engagement. Current Issues in Education, 14 (1). Retrieved from http://cie.asu.edu Turner, J. & Herren, R. V. (1997). Motivational needs of students enrolled in agricultural education pro grams in Georgia. Journal of Agricultural Education, 38 (4), 30 41. doi:10.5032/jae.1997.04030 Wigfield, A., & Wentzel, K. R. (2007). Introduction to motivation at school: Interventions that work. Educational Psychologist, 42 (4), 191 196. Willms, J. D., Fr iesen, S., & Milton, P. (2009). What did you do in school today? Transforming classrooms through social, academic, and intellectual engagement (First National Report) Toronto: Canadian Education Association.

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150 BIOGRAPHICAL SKETCH Ashley Nichole Young grew up in Miami, Florida were she was enrolled in the Agriscience magnet program at Coral Reef High School. During her studies as a high deepened. While in high school Ms. Young was an ac tive FFA member, 4 H member, and was active with her local county fair serving as an ambassador and lead ambassador her junior year After graduating high school in 2006 Ashley was elected to serve the Florida FFA Association as the Area VI State Vice President. It was durin g her year of service that Ms. Young discovered her passion for teaching After retiring as a state office r in 2007 she moved to Gainesville, Florida w h ere she enrolled in Santa Fe Community College. Ashley received an Associate of Arts degree in a gricultur e from Santa Fe Community C ollege in the spring of 2009 and enrolled in the Agricultural Education and Communication program at the University of Florida in the fall. s degree Ashley was active in many school organizations incl uding Collegiate FFA, Collegiate Farm Bureau, Alpha Zeta, and Alpha Tau Alpha. Ashley gradua ted with a Bachelor of Science d egree from the University of Florida in the spring of 2011. During the fall of 2011 she began her graduate work in Agricultural Edu cation at the University of Florida and became a middle school agricultural educator and FFA advisor teaching Exploratory Agriscience at High Springs Community School in High Springs, Florida In 2012 Ms. Young was awarded the Rookie Teacher of the year a ward for Alachua County Career and Technical Education and at High Springs Community School. Upon graduating with her Master of Science degree in a gricultural

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151 e ducation Ashley plans to continue her teaching career with the hopes to continue to influence, inspire, and motivate students through agricultural education.