1 DEVELOPMENT OF THE SCHOOL ACHI EVEMENT AND MOTIVATION SCALES: AN ASSESSMENT TOOL USED TO DIFFE RENTIATE REASONS FOR STUDENT UNDERACHIEVEMENT By CAROLYN SKINNER A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008
2 2008 Carolyn A. Skinner
3 To my parents, for all of th eir encouragement and support.
4 ACKNOWLEDGMENTS I would like to sincerely tha nk Dr. Larry Loesch, the chair of my doctoral committee, for his constant encouragement and support through this lengthy process. Dr. Loesch served as both my mentor and role model. His wisdom and unde rstanding helped me persevere, even when I felt like giving up. I would also like to thank th e members of my committee. Dr. Ellen Amatea fostered the growth of my ideas and nurtured me through the beginning phases of my dissertation. Dr. Mary Ann Clark gave me valu able insights and opportun ities in the field of Counselor Education that motivated me to keep pursuing my goal of becoming a future Counselor Educator. Dr. Fran Vandiver provided me with the oppor tunity to put my ideas into practice at P.K. Yonge. I will be forever gratef ul to all of these wonderful educators for the support they have provided. I would also like to thank all the teachers and counselors who assisted me in the data collection process. These educators work incred ibly hard with their students, yet they were willing to give up more of their time to help me. Thank you Dr. Allan Etzkin, Teresa Leibforth, Denise Lugris, Debrah Klein, Courney Solder, Sue Mehok, Tara Smith, Aprille Dallape, Arthur Pumpian, Christina Thorn, Amy Murphy, and everyone else who helped out in some way! I truly appreciate all of their willingness and support. I would also li ke to offer my thanks to all the students who took the time to take my survey, and to their parents and guardians for allowing their child to participate. Finally, I would like to expre ss gratitude to my friends and family. I thank all of my friends, both near and far, for always being ther e for me. Thanks to Kelly and Mandy for being like the sisters I never had. Thanks go to Joseph, for his constant love an d support. I thank my brothers, Jeff, Paul, and Tim, who all served as an inspiration for my study in more ways than one. I would especially like to express appreciation to my parents, John and Deb, who have
5 sacrificed so much to help me get to where I am today. They are my role models, my inspiration, my support, and I am truly blessed to have them in my life.
6 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........8 ABSTRACT....................................................................................................................... ..............9 CHAPTER 1 INTRODUCTION................................................................................................................. .11 Scope of the Study............................................................................................................. .....12 Theoretical Framework.......................................................................................................... .14 Need for the Study............................................................................................................. .....16 Purpose of the Study........................................................................................................... ....17 Research Questions............................................................................................................. ....18 Definition of Terms............................................................................................................ ....18 Organization of the Remainder of the Study..........................................................................19 2 REVIEW OF THE RELATED LITERATURE.....................................................................20 Prevalence of Student Underachievement..............................................................................22 Outcomes of Underachievement.............................................................................................23 Need for the Study............................................................................................................. .....25 Theoretical Perspectives....................................................................................................... ..30 Macro Theories of Underachievement............................................................................30 Micro Theories of Underachievement.............................................................................33 Differential Theories of Underachievement....................................................................35 Theories Addressing Identificati on of Underachieving Students....................................38 Summary........................................................................................................................ .........41 3 METHODOLOGY.................................................................................................................4 2 Population..................................................................................................................... ..........42 Sampling Procedures............................................................................................................ ..43 Instrumentation................................................................................................................ .......45 Data Collection Procedures....................................................................................................4 8 Research Questions............................................................................................................. ....49 Methodological Limitations....................................................................................................5 0 4 RESULTS...................................................................................................................... .........52 Sample Demographics............................................................................................................ 52 Research Questions............................................................................................................. ....53
7 5 DISCUSSION................................................................................................................... ......75 Limitations.................................................................................................................... ..........75 Evaluations of Research Questions........................................................................................77 Implications................................................................................................................... .........80 Implications for Theory...................................................................................................81 Implications for Practice..................................................................................................82 Recommendations...........................................................................................................84 Summary........................................................................................................................ .........85 APPENDIX A LETTER OF INVITATION...................................................................................................87 B IDENTIFYING PARTICIPANTS..........................................................................................88 C INFORMED CONSENT LETTER........................................................................................89 D SCHOOL ACHIEVEMENT AND MOTIVATION SCALES..............................................91 E DIRECTIONS FOR TAKING THE SURVEY......................................................................97 F SURVEY ADMINISTRATOR C ONFIDENTIALITY AGREEMENT................................98 LIST OF REFERENCES............................................................................................................. ..99 BIOGRAPHICAL SKETCH.......................................................................................................105
8 LIST OF TABLES Table page 4-1. Respondent characteristics by gender and grade level..........................................................61 4-2. Means for respondent national norm percen tiles for Mathematics and Language (English) standardized test scores and means for Mathematics a nd Language Arts grades........62 4-3. SAMS factor loadings following the initial principal components factor analysis...............63 4-4. SAMS varimax rota ted factor loadings.................................................................................66 4-5. SAMS total and subscale summary statistics........................................................................69 4-6. Subscale structure of SAMS............................................................................................... ...70 4-7. Subscale means and standard de viations for grade level and gender....................................72 4-8. Four by two (grade level by gender) factoria l analysis of variance for subscale scores.......73 4-9. Correlations among respondent subscale scores, grade point averages, and standardized test percentiles..............................................................................................................7 4
9 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DEVELOPMENT OF THE SCHOOL ACHI EVEMENT AND MOTIVATION SCALES: AN ASSESSMENT TOOL USED TO DIFFE RENTIATE REASONS FOR STUDENT UNDERACHIEVEMENT By Carolyn Skinner August 2008 Chair: Larry C. Loesch Major: School Counseling and Guidance Many researchers have studied possible cause s for underachievement with the hope that their findings will help educators work more e ffectively with students who underachieve. While these researchers theories are insightful, almost all of their ideas are con ceptual and have little or no supporting empirical evidence. The School Achievement and Moti vation Scales (SAMS) were developed to investigate empirically the reasons students underachieve. Once the SAMS is established as valid and reliable it can be used to assist scho ol counselors in determining the reasons underlying a students underachievement. When the reasons for underachievement are better understood, school counselors a nd researchers will be able to evaluate inte rvention plans that directly address those reasons. This study involved 388 student participants in grades six through nine who completed the SAMS online. A school counselor or teacher provided school data, including grades and standardized tests scores, for 328 of these participants. A five f actor structure emerged from the SAMS. Subsequently, these five factors were treated as subscales of the SAMS: (I) Dedication to Schoolwork, (II) Personal Well-Being, (III) In terpersonal Diplomacy, (IV) Desire to Learn and Succeed, and (V) Academic Self-Concept. Differences in responding on each subscale by
10 grade level and gender were examined. In general, there were no gender based differences in responding, and attitudes about sel ected aspects of underachievement decreased as school level increased. Future studies should continue empiri cal investigations on th e SAMS to facilitate school counselorsÂ’ work with underachieving students.
11 CHAPTER 1 INTRODUCTION School counselors work with students [by] an alyzing and evaluating studentsÂ’ abilities, interests, skills and achievement. Test info rmation and other data are often used as the basis for helping students develop immediat e and long-range plans. (American School Counselor Association, 2003, p. 41) Certainly studentsÂ’ standardized test data are among the types of data with which school counselors work and about which they should be con cerned. This is especially true currently in light of the great emphasis on standardized test results and the accompanying significant implications for schools, school systems, a nd indeed schooling in America. Statewide standardized testing in partic ular, as an educational trend, has swept quickly throughout the United States. Florida and Texas are two states that served as forerunners to implement statewide, large-scale testing programs, and other stat es have followed their le ad (Amrein & Berliner, 2002; Flores & Clark, 2003). However, while some educational theorists and policy makers believe such testing will affect education positively for all studen ts, others are far less optimistic. Because of the current emphasis on each sc hoolÂ’s test results, and the accompanying potential penalties for low performance, schools ar e now Â“teaching to the testÂ” more than ever; that is, they are utilizing instru ctional activities designed specifically to enhance test results for the entire school. Typically, the vast majority of these intensified or modified instructional practices are aimed at Â“low pe rformingÂ” students, based on the assumption that they have the greatest potential for gain in their test scores. Unfortunately, similar instructional activities to increase statewide test performance in partic ular and academic performance in general for average and/or high performing students are rela tively rare. Apparently, average and high performing students either are presumed to have less chance to improve (i.e., the gains to be achieved do not warrant the effort needed to achie ve the gains), do not need to improve, or both. Therefore, unfortunately, one possible, and proba bly likely, outcome of la rge-scale (especially
12 high-stakes) testing is that students who are achie ving in the average range of performance levels are being Â“ignoredÂ” because school personnel ar e focusing their energies and resources on students who perform at the lowest achievement le vels rather than trying to meet the needs of all students (as is recommended by the American School Counselor Association [ASCA]). Somehow, there seems to be an underlying assu mption that students ach ieving at average or above average levels will be able to succeed in school on their own. It is obvious that there ar e many students who are performi ng at average levels and who are not failing standardized test s, but who nonetheless need and would benefit from Â“extraÂ” or Â“specialÂ” support, help, and specialized instruction. These students appear to be doing as well as they can or should academically, but actually ar e not performing up to th eir potentials. There also are many students who although they do well on standardized tests, fail their classes or do as little regular schoolwork as po ssible. These students are Â“ underachieving,Â” and need more attention in schools. However, because of the intense focus on standardized testing in schools today, and the concurrent attention to low-perfor ming students, the academic and other needs of underachieving students are often overlooked. Clearly these stude nts also would benefit from greater attention. However, before such attentio n can be given, more must be learned about who and what they are, that is, better ways to understand them must be developed. Scope of the Study There are many students who underachieve a nd therefore there is a great need to determine the best ways to serve them. Bruns (1992) worked with underachieving students he called Â“work-inhibited.Â” He found that by the seventh grade, 24% of students were underachieving. Estimates of underachieving stud ents range between 15 and 50% for gifted students (Ford & Thomas, 1997; National Co mmission on Excellence in Education, 1983;
13 Whitmore, 1980). Similarly, Seeley (1993) estimat ed that 15 to 40% of gifted students are at risk for underachievement. Preckel, Holling, and Vock (2006) compared the results of 93 students, all between 7th and 10th grade, on an intelligence test and their gr ade point averages. These researchers used a regression analysis model to compare the student sÂ’ intelligence test scores with grade point averages, and determined that 16% of th e 93 students were underachieving. Students at risk of dropping out also show a high level of underachievement. For example, the Center for Applied Motivation (CAM) is an or ganization to help failing students (Center for Applied Motivation, 1998-2004). Th e average intelligence quotient (IQ) for students utilizing the CAM services is 126, a well-above average score but students in CAM are brought in because they are failing (Spevak & Karinch, 2000). Underachievement has been shown to be linked to long-term problems. For example, longitudinal studies have shown that students who underachieve ar e more likely to be at lower level job positions (McCall, Evahn, & Kratzer, 1 992). Researchers also have compared gifted underachievers to gifted achievers. For ex ample, Peterson and Colangelo (1996) found both chronic and sporadic underachievement patter ns among gifted achievers and underachievers. Approximately 20% of the underachievers in their study were able to reverse academic underachievement patterns before graduation. In a follow up study, it was discovered that 41% of the underachievers improved academically after high school. However, gifted achievers were more academically successful and secure a bout their career direction (Peterson, 2000). Juvenile delinquency also has been linked to underachievement (B rier, 1995; Mandel, 1997). This does not mean underachievement causes delinquency; however, the link between delinquency and underachievement needs attention.
14 Adolescence is an especially difficult time for students because of all the changes they experience. Researchers have f ound that underachievement is a significant problem for gifted students in grades seven through nine (Peterson & Colangelo, 1996). Therefore, the participants in this study were in grades si x through nine because students in this age group have been shown to have underachievement problems. Theoretical Framework The study of academic underachievement has been dominated by the assumption that underachievers are a relatively homogenous gr oup characterized by similar motivations, personality characteristics, and skill deficits. While researchers have of ten disagreed as to the particular personality, motivati onal, and behavioral correlate s characterizing underachievers, they shared the assumption that a common set of personality and motivational correlates would differentiate underachieving from achieving students (e.g., Baker, Bridger & Evans, l998; Claes & Salame, l975; Davids & Sidma n, l962; Frost, Marten, Lahart & Rosenblatt, l990; Hinshaw, l992; Matsunaga, l977; Sepie & Keeling, l978 ; Simmons & Bibb, l974; Snider & Linton, l964; Van Boxtel & Monks, 1992; Wesley, l994). In recent years some theorists have challe nged the assumption that underachievers are a homogenous group (e.g., Mandel & Marcus, l988, l995; Peters, 2000; and Spevak & Karinch, 2000). These theorists contend th at underachievers are a hete rogeneous group who have in common limited academic performance, but who vary in their personality structures and motivational and behavioral patterns. Therefor e, rather than viewing underachievers as a homogenous group sharing a common set of personali ty or motivational ch aracteristics, these theorists propose that the motivation and persona lity characteristics of underachievers vary widely (but fall into predictable categories).
15 Mandel and Marcus (l988, 1995) suggested that underachievers differ from one another in their basic personality structure. These theo rists also hypothesized th at peoplesÂ’ behaviors are purposeful. Thus, an individualÂ’s motivation, not just the individua lÂ’s behavior, is the critical element for differentiating among underachievers as well as between underachievers and achievers. Linking different underachievement patte rns to major personality types (as defined by the DSM-III-R), Mandel and Marcus (l988, 1995) initially proposed a typology of underachievers consisting of five types. Howeve r, they later included an additional type. They identified the respective types as the: (a) Co aster, (b) Anxious Underachiever, (c) IdentitySearcher, (d) Wheeler-Dealer, (e) Depressed Un derachiever and (f) De fiant Underachiever. Spevak and Karinch (2000) also concep tualized underachievers as a heterogeneous group. However, they focused on examining how underachieving studen ts differed from one another in terms of thei r attitudes toward their schooling. Th ey proposed a four part typology of underachievers based upon differences in motiv ational characteristic s, including the (a) Â“unmotivatedÂ” student, (b) student lacking self -confidence, (c) indifferent student, and (d) student having problems with re sponsibility and authority. Peters (2000) also recogni zed the importance of re-concep tualizing underachievement in a more differentiated way. She theorized that unde rachievers could be dis tinguished in terms of a profile of varying behavior s and personality tendencies, and proposed six types of underachievers to encompass differing personality and behavioral profiles including the (a) IfThen, (b) Chameleon, (c) Disorganized, (d) Mani pulative, (e) Here Today, Gone Tomorrow, and (f) Rebellious student. These recent underachievement t ypologies present new and innovative conceptualizations. Therefore, they were examined carefully w ithin the context of development
16 of the School Achievement and Motivation Scales (SAMS) (Amatea & Skinner, 2006). More importantly here, they constituted the basis of the theoretical foundation for this study. Need for the Study Some researchers have worked to defi ne underachievement be tter (Reis & McCoach, 2000) while others have attemp ted to provide counseling in terventions for underachieving students (Fehrenbach, 1988; Martin, Marx, & Martin, 1980; Rathvon, 1990). Unfortunately, much of this research is framed within histor ic perspectives on and conceptualizations of underachievement, and therefore is of limited value. Given that current perspectives hold that underachieving students are a heterogeneous group, school counselors need to take into account more recent information in order to provide fully effective counseling interventions for underachieving students. For example, if the assumption of heterogene ity is supported, school counselors cannot continue to provide interventions base d on the assumption that all underachieving students possess the same or similar needs and/or will benefit from the same or similar interventions. Obviously newer approa ches to and interventions for underachieving students must incorporate efficient and effectiv e means of obtaining useful information about those students. School counselors are already burdened with many different work mandates. Therefore, to suggest that they take extensive time to iden tify the individual needs of each underachieving student would be frivolous because it would be an insurmountable task given their typical workload. Instead, needed is a psychometrica lly sound measurement tool that school counselors can use to identify underachieving studentsÂ’ needs easily and effi ciently. For ease of use, it should be a survey that asks underachieving stud ents about their persona lity characteristics, beliefs, and attitudes. With the information derived from such a measurement tool, school counselors could design counseling interventions that fit studentsÂ’ needs more effectively.
17 Conversely, if such a measurement tool cannot be developed, school counse lors could be advised to seek out other methods to identif y the needs of underachieving students. Obtaining information from which to better understand the heterogeneity of underachieving students also will add to the counseling literature by facilitating enhancement of available information about underachieving studen ts. In addition, a measurement instrument that would enable understanding of underachieving st udents within the c ontext of current theoretical perspectives would facilitate future research on both theore tical perspectives of student underachievement and interven tions that could be based on them. Purpose of the Study Historically, interventions to assist underach ieving students have attempted to meet the needs of all underachieving students by assuming th at all underachie ving students are homogenous. However, more recently, some researchers have come to believe that underachieving students have differe ntial personality char acteristics, attitudes, and beliefs that affect their academic achievement in various a nd often unique ways. So me have even gone so far as to propose different t ypologies that identify the comp onents of their personalities, attitudes, and beliefs (Mandel & Marcus, 1995; Peters, 2000; Rimm, 1995; Spevak & Karinch, 2000). However, there is scant empirical evid ence to support these theoretical propositions about the differences among underachieving students Further and more importantly here, there also is no sound and validated method that school counselors can use to measure the components of the uniqueness of underachieving students. A valid, reliable, and appropriate assessmen t measurement tool is crucial for school counselors so they can identify the reason(s) behind studentsÂ’ underachievement, develop commensurate intervention plans, and ultimat ely help underachieving students perform academically at appropriate levels. Therefore, the major goal of this study was to develop the
18 SAMS further. More specifica lly, the purpose of this study was to determine the psychometric properties of the SAMS based on data derived from a sample of students in grades six, seven, eight, and nine. The SAMSÂ’ item, subscale, and total scale psychometric properties were determined, as was its factor structure. Initial differential validity information also was garnered. Research Questions The following research questions we re addressed in this study: 1. What is the factor structure of the SAMS? 2. To what extent does the determined fact or structure confirm the proposed, theoretical structure? 3. What are the reliability coefficients for each of the SAMSÂ’ subscales? 4. What are the age group or gender differences in SAMS subscale scores? 5. What are the relationships between su bscale scores on the SAMS and student achievement? Definition of Terms The following is a list of terms used in th is study, in addition to their definitions. Underachieving students have been defined in many ways, but the definition used in this study is from Reis and McCoach (2000): Underachievers are students who e xhibit a severe discrepancy between expected achievement (as measured by st andardized achievement test scores or cognitive or intellectual ability as sessments) and actual achievement (as measured by class grades and teacher evaluations). (p. 157) Achieving students are those who are performing as expected, meaning that their measured achievement (as measured by a standardized achievement test) is commensurate with their classroom achievement (e.g., grades). Commensurate is used here to mean that a studentÂ’s classroom grade point average is wi thin one-half standard deviation from the studentÂ’s grade point average as predicte d by a standardized achievement test. Underachievement Typologies are theories of student underachievement that posit categories of distinction among individual underachieving students These typologies typically include consideration of personali ty characteristics, beliefs, and/or attitudes underachieving students use to view the world to group them into categories.
19 Sixth grade is defined as students who ar e currently attending the 6th grade in the United StatesÂ’ school system. These student s must be either ages 11 or 12. Seventh grade is defined as students who are currently attending the 7th grade in the United StatesÂ’ school system. These student s must be either ages of 12 or 13. Eighth grade is defined as students who are currently attending the 8th grade in the United StatesÂ’ school system. These students mu st be either ages of 13 or 14. Ninth grade is defined as students who ar e currently attending the 9th grade in the United StatesÂ’ school system. These students must be either ages of 14 or 15. These four grade levels were chosen because they correspond with the ages when underachievement is considered to be more apparent and widespread (Peterson & Colangelo, 1996). School counselors are employed school personnel whose jo b is to help students learn more effectively, but not through dire ct classroom instruction (ASCA, 2003). Rather, school counselors team with other school personnel to identify students who need special attention and to find resources and/or devel op intervention plans to help these students overcome obstacles to learning. The school coun selors in this study must have earned a masters degree in school c ounseling and hold state-leve l professional certification. Organization of the Remainder of the Study The remainder of the study is divided into f our chapters. Chapter 2 is the review of the literature related to the study. Th e methodology is described in chap ter 3 and the results of the study are presented in chapter 4. Chapter 5 provi des the discussion, conclusion, implications, and recommendations.
20 CHAPTER 2 REVIEW OF THE RELATED LITERATURE It is desirable to define unde rachievement clearly pr ior to delving further into the topic. This may seem like a simple task; however, a professional consensus on a definition does not exist (Reis & McCoach, 2000). Commonly, un derachievement has been defined as Â“performance which does not measure up to an individualÂ’s level of aptitudeÂ” (Chaplin, 1975, p.556) or as Â“performance below the Â‘expected le velÂ’ indicated by that individualÂ’s performance on ability or aptitude testsÂ” ( American Heritage Dicti onary of the English Language 1973, p. 1395). While such definitions provide a perspective for defining underachievement, they are not specific enough for use in actua lly identifying un derachievers. Traditionally, researchers have identified unde rachieving students by comparing their test scores in a certain area (e.g., inte lligence, achievement, aptitude, or general cognitive ability) and academic performance indicators for them (e.g., gr ades) (Colangelo, Kerr, Christensen & Maxey, 1993; Preckel et al., 2006; Supplee, 1990; Whitmore, 1980). In this approach, if studentsÂ’ grades or scores on cognitive ability m easures are lower than their m easured academic performance by a substantial amount, they are consider ed Â“underachievers.Â” For exampl e, if a student tested in the 90th percentile of an intelligence test but had a 1.5 (out of 4.0) gr ade point average, s/he would be considered an underachiever beca use the cognitive ability measur e would predict a much higher grade point average for the student. These types of definitions provide guidance for identifying underachieving students. Preckel et al. (2006) used a regression anal ysis model to identify underachieving students in Germany. StudentsÂ’ scores on a general intelligence test were compared with their respective overall grade point averages fr om the past three years. St udents were viewed to be underachieving if their intelligence scores were greater than one sta ndard deviation from the
21 predicted score based on the stud entsÂ’ grade point average. In other words, if a studentÂ’s intelligence score was at least one standard devia tion higher than his/her predicted grade, then the student was considered to be an underachiever. Reis and McCoach (2000) analyzed definitions of underachievement from three decades of research and proposed their own definition of underachievement: Underachievers are students who exhibit a severe discrepancy between expected achievement (as measured by standardized achievement test scores or cognitive or intellectual ability assessments) and actual ach ievement (as measured by class grades and teacher evaluations). (p. 157) Within this definition, studentsÂ’ scores on achie vement tests can be compared to studentsÂ’ actual achievement in school. In effect, a studentÂ’s measured potential for academic performance is compared to actual academic pe rformance. This definition is reasonable and logical, and therefore was the basis of the definition used for this study. Unfortunately, however, although helpful, Reis and McCoachÂ’s definition of underachievement does not distinguish between underachievers and students with learning disabilities or other disorders that may inhibit aca demic performance. Therefore, it is important to distinguish between students with a lear ning disability (LD) and students who are underachieving. Learning disabiliti es or other disorders (e.g., A ttention Deficit Disorder) may cause a student to present as underachieving when in fact the studentÂ’s underperformance is a result of his/her disability (Spevak & Kari nch, 2000). Conversely, an underachievement or motivational problem may mask a learning di sability (Reis & McCoach, 2002; Siegle & McCoach, 2005). Even more unfortunately, so me underachieving students suffer from both a learning disability and motivational probl ems (Green, 1989; Mandel & Marcus, 1995).
22 Prevalence of Student Underachievement While the definitions of underachievers that have been used differ, it is evident from previous research that underachievers compri se a large proportion of the current student population in American schools. For example, Bruns (1992) identified st udents who should have been performing better in school, which he labeled as Â“work-inhibited.Â” He found that there are many students in grades three th rough twelve who could be doi ng better academically, but their lack of effort caused them to underperform in school. In particular, he found that between 416% of elementary school students were work-i nhibited, but by seventh grade, 24% of the students were identified as work-inhibited. Pr eckel et al. (2006) f ound that 16% of the 7th-10th grade students in their study were underachieving in school. The Center for Applied Motivation (CAM) is an organization to help failing (presumably underperforming) students (Center for Applie d Motivation, 1998-2004). The CAM reported that about 85% of students with motivational proble ms are between the ages of 8 and 18. The average intelligence quotient (deviation IQ) for students utilizing the CAM services is 126, a well-above average score. However, CAM student s are failing their courses in school (Spevak & Karinch, 2000). Another source of evidence for the prevalen ce of underachievement is the research on gifted students. There is a lack of c onsensus on how to best define and measure underachievement, and therefore it is diffi cult to estimate how many gifted students underachieve. However, resear chers studying gifted underachie vers have estimated that anywhere between 20 and 50% of gifted students underachieve (Ford & Thomas, 1997; National Commission on Excellence in Education, 1983; Preck el et al., 2006; Whitmore, 1980). Further evidence of gifted underachievement comes from statistics on school dr opouts. Gifted students have been estimated to comprise between 18 and 25 percent of high school dropouts (Renzulli &
23 Park, 2000; Rimm, 1995; Robert son, 1991; Solorzano, 1983). However, Matthews (2006) cautions researchers on the inte rpretation of these data beca use of varying methods for identifying both Â“dropoutsÂ” and Â“giftedÂ” student s. However, Richert (1991) suggested that reported percentages for gifted underachieving stude nts are underestimates because of the use of IQ scores as criteria. That is, Richert noted that using IQ scores alone does not allow for effective identification of certain types of gifted students, and therefore more students could, and likely would, be included in the gifted-but-underachieving group. While the percentages of students who underach ieve cannot be determined precisely, it is evident from available research that underachievement is a problem prevalent in schools today. The available data demonstrate the problems with failing gifted students, yet there are far more students with similar problems not accounted for because they are not in populations that gain attention from researchers. Typically, these students maintain a moderate (but not failing) grade point average when in fact they are capable of doing much better. Thus, there are many students who Â“slip between the cracksÂ” because they are no t noticed by educators, researchers, and other professionals. Outcomes of Underachievement While it is evident that unde rachieving students struggle in school, what happens to them when they are done with school is an even more important question. Does studentsÂ’ underachievement in school affect their lives substantially and significantly? McCall, Evahn, and Kratzer (1992) followed over 4,000 high school students after graduation and compared low achievers, underachievers, and hi gh achievers. They found that underachievers had lower level job positions than achievers. Fu rther, the underachievers who had performed two or more grades below expectations in school neve r caught up to their achieving p eers. A small percentage of
24 underachievers were able to catch up, but those st udents were from families with highly educated parents; presumably they subsequently gained the desire to achieve. Peterson (2000) compared a group of 73 gift ed achievers and under achievers post high school graduation. She found that four years after high school, gi fted achievers had completed more college, had higher college grade point averag es (GPAs), and were more certain about their career directions. However, she also found that 26 percent of the underachievers had at least 3.0 GPAs in college. She concluded that some gifted underachievers began to achieve in college, at least for those who went to college after high school. Some research supports an associa tion between juvenile delinquency and underachievement (Mandel, 1997). For example, low grades (attributed to underachievement) have been associated with delinquency by the en d of elementary school (Brier, 1995). Further, this relationship has been shown to hold for a dolescents who are both system-labeled and selfreported as being Â“delinquentsÂ” (Dishion, Lo eber, Stouthamer-Loeber, & Patterson, 1984). However, it remains unclear as to wh at extent, if any, underachievement causes delinquency. Other confounding factors might cause an underach ieving student to commit acts of delinquency. For example, hyperactivity and ADHD can play a role in the development of underachievement (Mandel, 1997) and Conduct Disorder has been diagnosed in approximately 45 percent of teenagers with ADD (Zeigler-Dendy, 1995). Th e complex interplay among ADHD, Conduct Disorder, other disorders, and unde rachievement makes it difficult to determine which factors are causal. However, whether underachievement leads to delinquency, or vice versa it is apparent that the problem of delinquency a nd underachievement needs attention. Underachievement can be a problem for all stude nts at any time in their lives. However, the turbulence adolescents experience through their search for identity makes adolescence an
25 especially difficult time for them. For example, researchers have found that underachievement is a significant problem for gifted students in the early years of adolescence (Peterson & Colangelo, 1996). It is not surprising that students in this age gr oup have a difficult time with underachievement because it is a time period when children begin to develop and form their own identities, and thus are often focused on self -concerns other than academic performance (Erikson, 1950; Marcia, 1966). The im plication of this information is that underachievement is a significant problem for students in grades 6 through 9. Need for the Study School counselors have approached worki ng with underachieving students in different ways. For example, some school counselors do not separate low achieving students from underachieving students in their sc hool counseling activ ities, opting instead to consider all students as having Â“equal educat ional potential.Â” Thus, thes e school counselors form and administer intervention plans for these two populations of students as if th ey are all experiencing the same circumstances. For example, Newsome ( 2005) sought to determin e the effectiveness of solution-focused brief therapy w ith Â“at-riskÂ” students and found that it significantly improved their social and academic behaviors. The results are tenuous however, because the students who participated could have been low achieving and/ or underachieving, but were not so differentiated in the study. Similarly, Cook and Kaffenberger (2003) developed a c ounseling and study skills program, and tested it with middle school studen ts who failed two or more classes. These students may have been lowor under-achieving, but no clear distinction was made among them. All students in this group were provided the same intervention. At th e end of the study, the studentsÂ’ grade point averages we re examined. It was found that 11 of the 16 participants had higher grades afte r the intervention.
26 Rathvon (1990) compared the effects of an examination preparation unit in smalland large-group formats on the performance of lowand under-achievers. Rathvon acknowledged the difference between underand low-achieving students, but did not differentiate between the two groups in her results. This intervention di d not yield significant changes based on the examination preparation method employed. More recently, Webb, Brigman, and Campbell (2005) had 418 students participate in group counseling sessions intended to improve student achievement. Student Success Skills (SSS) were taught in the gr oup counseling sessions. The SSS program was developed to improve academic and social outcomes for students. This study attempted to improve student achievement in general and no differentiati on was made between lowand under-achieving students. The researchers assumed that th e SSS would improve the studentsÂ’ achievement behaviors regardless of the basi s of their underachievement. The results included that studentsÂ’ scores on a statewide standardiz ed test improved significantly in math but not in reading. It is important for school counselors to try to improve student achievement because that goal is central to the school counseling prof ession (American School Counselor Association, 2003). In addition, school counselors now more than ever are trying to prove that the school counseling interventions they use will improve student achievement because of increasing pressure to be accountable for their activities. These attempts to improve student achievement and show accountability are positive advances in the field of school counseling. However, it is important to begin to formulate intervention plans to improve student achievement more carefully. Students who are high -, low-, or under-achievers ca nnot be placed blindly into identical intervention plans. Each student need s to be viewed as a uni que individual and not solely as part of a large group of students whose scores or grades need to improve. Some school
27 counseling professionals recognize the importa nce of differentiating underachieving students from high and low achieving students as they addr ess the individual needs of underachievers to investigate what school counselor s can do specifically to help students change patterns of underachievement. Unfortunately, research in the school counsel ing profession on under achievers typically has relied upon traditional, rather simplistic conceptualizations about underachieving students. Specifically, the study of academic underachievement has been dominated by the assumption that underachievers are a rela tively homogenous group characterized by similar motivations, personality characteristics, and skill deficits. Thus, while researchers may have disagreed as to the particular personality, motiva tional, and behavioral correlat es characterizing underachievers, they apparently shared the assumption that a common set of persona lity and motivational dynamics differentiate underachieving from achievi ng students. Illustrati ve of this line of thinking is the work of researchers who assu med that anxiety plays a central role in underachievement. For example, using the Genera l and Test Anxiety Scales for Children and a mathematics anxiety scale, Sepie and Keeli ng (l978) found that underachievers scored significantly higher on math anxiety than ach ieving or overachieving 11 and 12 year old children. Simons and Bibb (l974) also used test anxiety and need for achievement measures with a small group of male and female fourth to sixt h graders and reported that fear of failure was closely associated with underachievement. In recent years, researchers have refined such research by studying links among fear of failure, anxiety, perfectionism, procrastination, and academic underachievement. For example, Frost, Marten, Lahart and Rosenblatt (l990) ex amined the relationships among studentsÂ’ overconcern with making mistakes, parental expectations and criticism, setting high personal
28 standards, procrastination behaviors, and academic achievement. Similarly, Wesley (l994) studied the relationships between ability level, high school achievement, and procrastination behavior. Other researchers emphasized and examined diffe rent sets of psychosocial correlates (e.g., impulsivity, self control, aggres siveness, or prosocial skills) in the attempt to differentiate achievers from underachievers. Snider and Li nton (l964), for example, in a comparison of California Psychological Inventory (CPI) sc ores of achieving and underachieving 10th and 11th graders, found that achievers were better adjusted and tended to be more socially and personally responsible. Davids and Sidman (l962) co mpared achieving and underachieving high school boys and found that the achieving ma le students had greater self-c ontrol over impulses and were more oriented toward the future, less concer ned with immediate gr atification, and more concerned with future plans than were the undera chievers. This line of thinking also has been pursued by contemporary researchers who have demonstrated strong linkages in school-age children between academic underachievement and an tisocial behavior and attention deficits (e.g., Hinshaw, l992; Lane, 1999). Still other researchers attempted to differen tiate achieving from unde rachieving students by examining global self-concept or specific self-repo rted characteristics. For example, Claes and Salame (l975) found that secondary school unde rachieversÂ’ self-evalu ations had cognitive differences from those of achievers. Specifically underachievers were more self-critical and less accurate in self-evaluations, and did not intern alize high standards for academic performance. Matsunaga (l977) gave the Self-Concept of A cademic Ability, Importance of Grades Scale, Attitudes Toward Mother, Attitudes Toward Father, Checklist of Trait Names, STS Youth Inventory, and the California Psychological Invent ory to high school students. He found that
29 achievers had higher self-concept of ability, better attitude toward achievement, more positive image of teacher perceptions, concern with good relationships, more self-confidence and responsibility, and greater awaren ess of the needs of others. In contrast, some researchers have not f ound a strong relationship between self-concept and underachievement. For example, Reisel (l971) gave a 60-item Q-sort to 17 achieving and 17 underachieving high school students and reported that achievers and underachievers could not be differentiated by particular person ality characteristics. Simila rly, Peters (l968) reported a nonsignificant relationship between self-concept and under achievement in a sample of 164 high school seniors. Yet despite such contradict ory findings, contemporar y researchers studying gifted underachievers continue to examine the role of self con cept in differentiating achieving and underachieving students (e.g., Baker, Bridge r & Evans, l998; Van Boxtel & Monks, 1992). How can sense be made of these seemingl y inconsistent and incongruous research findings? How can underachievers be characterized as anxious, perfectionistic, and depressed in some studies while depicted as aggressive, alienated, and impulsive in others? Which personality and motivational correl ates, if any, are correct? In recent years several theorists, notably Mandel and Marcus (l988; l995), Rimm (1995), Spevak and Karinch (2000), and Peters (2000), have attempted to reconcile the inc onsistencies and incongr uence among previous perspectives and findings. They contended th at contradictory profile s of underachievers are understandable only if the assumption is made that underachievers are a heterogeneous group who share a similar symptom of limited academic performance, but vary in their personality structure and motivational and behavioral pa tterns. Therefore, rather than viewing underachievers as a homogenous group with common personality and/or motivational
30 characteristics, they variously proposed th at the motivation, beha vior, and personality characteristics of underachievers differ, yet fall into pred ictable categories. Theoretical Perspectives Several theorists have provide d conceptualizations that facilitate understanding of students who underachieve. Some of these theories are couched in a macro perspective that explains adolescent identity development and th e influence of the family on underachievement. Others offer a micro perspective that facilitates understand ing of an individual studentÂ’s issues that might cause them to underachieve. The micr o theories include those that consider selfefficacy, self-regulation, and the stages of change students might be experiencing. Macro Theories of Underachievement Underachievement can be a problem for all st udents at any time in their lives. However, the turbulence adolescents experi ence through their search for an identity makes this an especially difficult time for them. For example, researchers have found that underachievement is an especially significant probl em for gifted students in gr ades 7 through 9 (Peterson & Colangelo, 1996). It is not surp rising that students between thes e ages have a difficult time with underachievement, or other behaviors, because th is age period marks a time when children are striving to develop into adoles cents and to form their own identities (Erikson, 1950; Marcia, 1966). AdolescentsÂ’ struggle in the search for an identity mi ght disrupt the learning process and cause students to underachieve. Erikson (1950, 1968) outlined a lifespan theory of human development. The stage during adolescence is labeled Â“Identity vs. Role Diffusion.Â” Thus, adoles cents are trying to search for who they are as an individual (Erikson, 1959). Ho wever, they also are concerned about how others (especially their peers) view them (Eri kson, 1968). Adolescents thus have to evaluate what they know about themselves in order to deve lop a definition of self. Such (adolescent) self-
31 knowledge evolves from the input the student has received thus far in his or her life. For example, if people consistently tell an adolescent that s/he is a smart person, the adolescentÂ’s self-definition likely will include an element of intelligence. Adolescents strive to establish an individual definition of self, and one that is different from the definition of self held in childhood. Du ring the childhood stages, identity is connected strongly to parentsÂ’ expectati ons (Erikson, 1968). However, as adolescents approach adulthood, they have a strong desire to be in dependent individuals and to be in charge of their own identity. Parental relationships have less importance during adoles cence; however, friendships gain importance as adolescents search for ne w people to love (Ame rican School Counselor Association, 2000-2002). Therefore, peer groups have significan t influence on adolescents as they try to separate themselves from their famil y. In addition, they continue to need to have important people in their lives a nd often turn to peers as those important people. Adolescents want to establish their own sense of identity whil e at the same time feeling a part of their peer group. During identity formation, adolescents are constantly evaluating themselves and whether their peers will approve of the identity they have created. MarciaÂ’s (1966) identity status theory also addresses the st ruggle people, including adolescents, experience in identity formation tasks. Marcia defined identity status along the dimensions of commitment and exploration: (a) Identity Achi evement, (b) Moratorium, (c) Foreclosure, and (d) Identity Diffusion. Theoretical ly, MarciaÂ’s identity statuses are appropriate for any age group, and therefore are suitable fo r explaining adolescent identity development processes. MarciaÂ’s theory describes id entity along two dimensions: exploration and commitment. An adolescent who has reached Identity Achievement will have both explored and committed to an identity. Adolescents in Moratorium have explored, but not yet committed, to
32 an identity. Adolescents in Foreclosure have committed to an identity without exploring, and those in Identity Diffusion have neither explored nor committed to an identity. Children who are just about to enter adolescen ce are likely to begin to experience identity diffusion or foreclosure, whereas adolescents later in the stage are more likely to be in the stages of moratorium or identity achievement. Therefore, adolescents who are in the Identity Achievement or Moratorium stages are psychologically more mature than those who are in the Foreclosure and Identity Diffusion stages (Marcia, 1966; Zuo & Cramond, 2001). Another factor in the under achievement of adolescents is the psychosocial systems in which they live. For example, adolescent ac ademic underachievement has been related to problems within the family (Rimm & Lowe 1988), school (Wills & Munro, 2000), peer group (Bruns, 1992), and even the individual (Lau & Chan, 2001). Green (1989) suggested that an ecological model is the most useful framew ork for understanding students who underachieve. This model assumes that achievement problems ca n be caused by issues in the family, school, or larger social context. Green developed several hypotheses to guide future research, the first of which was that children with information-proces sing deficits are mainta ined or exacerbated by intrafamily communication problem s. Second, childrenÂ’s attention deficit problems are made worse when their family is underorganized or chaotic. The third hypothesis assumed that childrenÂ’s opposition to or performance anxiety in relation to school tasks is maintained or made worse by families who are overorganized and rigi d. GreenÂ’s last hypothesis was that children lacking academic motivation maintain this behavi or more strongly when their family members make negative attributions about the childÂ’s abilities, blames the poor school performance (only) on factors external to the child, compares the childÂ’s school performance to siblings, and/or minimizes the importance of education.
33 Other researchers also have suggest ed an ecological approach to studying underachievement. For example, Baker, Bridge r, and Evans (1998) studied three models of underachievement and provided a general model to incorporate the three specific models. The various specific models were based on the influe nce of individual, family, or school factors. These researchers concluded that each model wa s significant individually and contributed to a studentÂ’s achievement, but that the combined mode l produced the strongest results. They further concluded that in order to understand and he lp underachieving students, family, school, and individual factors must be considered simultaneously. Micro Theories of Underachievement Bandura (1986) proposed that two mechanisms affect achievement: self-regulation and self-efficacy. In order for people to control thei r own behavior (i.e., sel f-regulate), they must first be attentive to aspects of their behavior (Bandura, 1986). For example, if students do not realize that they are going to fail a class because they never hand in their homework, they will be less likely to regulate their academic behavior. Therefore, in order for students to achieve appropriately academically, they first need to recognize personal behaviors likely to yield negative outcomes. Students may desire to change, but until they recognize their personal behaviors that influence change, thei r situations will remain stagnant. People sometimes act habitually, i.e., wit hout considering what they are doing or the consequences of their behavior. For example, a student who does not complete his or her homework may recognize the need to change. Ho wever, if the student has habits that make homework completion difficult (e.g., talking at length on the phone during time better spent studying, waiting until late at night to complete homework, or watching television while trying to do homework), the student is unlikely to be su ccessful academically. Habits such as these
34 obviously interfere with effectiv e academic preparation. However, because such behaviors are habitual, the student may have a hard time changing them. In regard to negative habitual behaviors, it is not until students are (relatively highly) motivated to change that change will in f act occur (Bandura, 1986); the value placed on a behavior affects whether a person de cides to change it. For example, if a student sees little or no value in achieving academically, s/he will not be mo tivated (to self-regulate) to get better grades in school. Lack of motivation has been f ound to be a significan t problem among and for underachieving students (Pos tlethwaite & Haggarty, 2002). Bandura (1986) defined self-efficacy as Â“p eopleÂ’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performancesÂ” (p. 391). Some people know exactly what behaviors they need to change and they have the desire to change the behaviors. However, if a person ha s low self-efficacy, s/he will be less likely to engage in behaviors that will l ead to success. Students who have developed confidence in their academic abilities are more likely to behave as if they are academica lly capable (McCoach & Siegle, 2003). Conversely, students who do not perc eive themselves as academically capable are unlikely to achieve academic success. The stronger a personÂ’s perceived self-efficacy, the more persistent the person is in trying to complete a task, and vice versa (Bandura, 1986). For example, students who have low selfefficacy in math will be less likely to persist in the attempt to solve a mathematics problem. Schools are an important agent in the cultivat ion of academic self-efficacy. For example, a classroom in which social comparison is encouraged will produce more students with low selfefficacy than one that encourages students to compare their progress to personal standards.
35 During adolescence, perceived self-efficacy b ecomes more differentiated as more skill areas are introduced and self-efficacy is establ ished for each area. This differentiation also typically leads to prioritiza tion among areas. For example, learning how to deal with heterosexual relationships often becomes more important in adolescence than is getting good grades (Bandura, 1986). Prochaska, Norcross, and Diclemente (1994) developed a theory of change in which the six stages people go through in making life changes are delin eated: precontemplation, contemplation, preparation, action, maintenance, and termination. Most underachieving students are in either of the first two stages. Precontemplators have no intention to change and typically deny that they have a problem. Contemplators acknowledge that they have a problem, but are not ready to take the steps n eeded to change. Yet while Contemplators acknowledge the problem, they are Â“stuck;Â” they generally know how to change but are not willing to take the necessary steps to bring about change (Prochaska, Norcross & Diclemente, 1994). Underachieving students need to pr ogress beyond the precontemplation and contemplation stages to prepare for and eventual ly take action to cha nge the behaviors that prevent them from achieving. When they do take action, typically they need continuous support to reach the maintenance stage. Unfortunately, this process is often a long and difficult. Further, even when they reach the maintenance st age, they need support le st they relapse to an earlier stage (Prochaska, et al., 1994). Differential Theories of Underachievement Mandel and Marcus (l988) were among the fi rst to propose a differential theory of underachievement. They suggested that underach ievers did not differ onl y in their level of academic motivation, but also in th eir personality structures. Defi ning personality structure as a meaningfully organized and interre lated set of personality traits motives, and behaviors, they
36 proposed a typology of underachievi ng students who differed from one another in their basic personality structures. Their initial proposal was a typology of five underachievement patterns linked to major personality types as defined in the DSM-III-R (American Psychiatric Association, 1987): (a) Overanxi ous Disorder, (b) Conduct Disord er, (c) Academic Problem, (d) Identity Disorder, and (e) Oppositional Defiant Di sorder underachievers. In a subsequent work, Mandel and Marcus (1995) revised their original typology to include an additional type they called the Â“Sad or Depressed Underach iever,Â” for a total of six types. Rimm (l995) differentiated under achieving students on the basis of specific and particular symptomatic behaviors. She hypothesized that underachievers diffe red along two continua: dependence-independence and dominance-submissi on. Combining these two dimensions into four combinations, she described four distinct types of underachie ver: (a) dependent conformer, (b) dependent nonconformer, (c) dominant c onformer, and (d) dominant nonconformer. Spevak and Karinch (2000) examined how underachieving students differed from one another in regard to their at titudes toward schooling. They theorized that it was studentsÂ’ attitudes, not their personality structure, that hindered them from achieving. They proposed a four-part typology of underachieve rs based upon differences in att itudinal characteristics: (a) Â“unmotivatedÂ” student, (b) student lacking self -confidence, (c) indifferent student, and (d) student having problems with re sponsibility and authority. Peters (2000) theorized that unde rachievers could be distinguis hed in terms of a profile of specific behaviors and attitudinal tendencies, an d proposed a model that included six types of underachievers: (a) If-Then Student, (b) Chamel eon Student, (c) Disorganized Student, (d) Manipulative Student, (e) Here Today, Gone To morrow Student, and (f) Rebellious Student.
37 Bleuer and Walz (2002) developed the Â“Couns eling Underachievers ModelÂ” to make the underachievement typologies more useful to school counselors. This model proposed that there are three variables that interact with one anothe r to lead students to perceive their academic ability as high or low. These variables also enc ourage or discourage students to desire academic achievement. The Bleuer and Walz variables include d: (a) external variables (e.g., family, peers, teachers, and task difficulty); (b) cognitive variables (e.g., mental ability, prerequisite knowledge, and past learning expe riences); and (c) affective variables (e.g ., disposition, psychological development, and values/goals). Bleuer and Walz (2002) suggested that school counselors collaborate with the st udents to determine a personalized intervention plan. They also developed a rating scale for use with the student to determine their Â“barriersÂ” and Â“assets.Â” According to Bleuer and Walz, barriers are to be addressed and confronte d, and use of assets is to be encouraged to help the student overcome underachievement. Bleuer and Walz (2002) also admonished school counselors to recognize the importance of differentiating among underachieving students in order to work with them effectively, and developed a model for applying th e typologies to the practice of school counseling. While such an approach is helpful in the application of contemporary theories of how to reduce underachievement, it remains important to consid er underlying theory prior to implementing any intervention. That is, although educators and school counselors can speculate that underachieving students fall into dis tinctive typologies, it is not yet fully established that various types of underachieving students actually exist. Therefore, there remains need for school counseling researchers to first determine types of underachieving students. To accomplish this, a measure needs to be developed that will help school counselors assess the characteristics, attitudes, and behaviors of unde rachieving students. Once this measure has appropriate and
38 sufficient psychometric properties, school and other counselors can use it as a basis for identifying types of underachievi ng students and develop appropria tely varied interventions. A fundamental assumption underlying this rese arch is that under achieving students are not a homogeneous group, but instead possess differ ential personality characteristics, attitudes, and beliefs. It follows that school counselors cannot work ef fectively with differing students using only one intervention plan or model because the students do not all share the same needs and/or reasons for underachieving. Theories Addressing Identification of Underachieving Students The theories presented that include typologi es of underachieving st udents resulted from development of Â“logicalÂ” categories into wh ich underachieving students may be placed (e.g., Mandel & Marcus, 1995; Rimm, 1995) However, while these theories seem reasonable, the use of these typologies through anecdotal examples of underachieving studen ts cannot be supported strongly based simply on intuition. Therefore, it is essential that a measure be developed that can determine, quantitatively, different types of underachieving students. Currently, no such measure exists. Researchers have developed chec klists and other simplistic methods to help educators determine areas in which underach ieving students may need assistance (Mandel & Marcus, 1995; Heacox, 1991). However, these met hods have not been evaluated for quality of their respective psychom etric properties. TeachersÂ’ identification is another method that has been used to determine which students do or will underachieve. Teachers can simply be asked to determine the underachievement typology in which a student fits. This methodol ogy is easy and available in schools, but asking teachers for such information is not without pr oblems. TeachersÂ’ opinions are by definition subjective, and therefore vary from one teacher to another. Clearly it is not the be st practice to rely solely on teacherÂ’s opinions for Â“concrete informationÂ” about a studentÂ’s underachievement
39 type; using teachersÂ’ evaluations and categorizations to assess underachievement types is not likely to withstand psychometric scrutiny. Educators most commonly identify under achieving students when they observe a discrepancy between the studentsÂ’ aptitude tests and gr ade point averages (Preckel et al., 2006). However, again, some students achieve low grades because of a learning disability or other disorders that cause them to under-perform. A quantitative assessment would help school counselors and educators determine if the stud ent is underachieving because of reasons beyond the childÂ’s control (e.g., a lear ning disability). If the true reason behind a childÂ’s underachievement is not identified accuratel y, effective treatment is not possible on any consistent basis. There also are other advantages to using a quantitative assessment to determine the bases for student underachievement. For example, it may appear that a student can get higher grades simply on the basis of increased effort when in fact a learning disability or other disability makes schoolwork very difficult. Similarly, there may be gifted students with relatively high grades yet who are actually underachieving because of lack of challenge in their education. They may not have to exert any effort to receive these grad es. An effective, quantitative assessment would help determine whether the student actually is underachieving, a nd if so, whether the underachievement is something ove r which the child has control. Another advantage is that an effective asse ssment could help school counselors determine efficiently the reasons underlyi ng a studentÂ’s underachievement including consideration of factors such as family and/or social valu es, motivation, commitment, self-management, confidence, or emotional state. It takes mu ch school counselor time to determine possible underlying underachievement. An assessment wo uld be a more efficient way to cover the
40 possibilities. Further, a school counselor working with under achievers should not plan or implement an intervention for a child until the bases of the underachievement are well understood. Therefore, the more efficien t the determination of the reasons for underachievement, the more quickly the stud entÂ’s underachievement can be addressed. There are, however, limitations to using an assessment instrument. For example, students in todayÂ’s schools are usually Â“bombarded with testingÂ” and may not be willing to take yet another assessment. If student s do not respond to the assessment appropriatel y, the results will not be accurate or useful. Another limitation is that an assessment only provides data from one person, the student. To achieve best understanding of a studentÂ’s underachievement, it would be most effective to gather data from other people such as the studentÂ’s teacher(s) and parent(s). Another limitation is that students may engage in social desirability responding to convey to how they would like to be viewed rather than how they would respond to the items truthfully, which introduces invalidity into the assessment. The American School Counselor Associati on advocates that school counseling programs be Â“data drivenÂ” (American School Counselor Asso ciation, 2003). An empi rical assessment that establishes the bases for a student Â’s underachievement enables school counselors to use data to improve the efficiency and effectiveness of servi ces they provide. In addition, the use of an assessment could enhance school counselor acco untability by allowing demonstration that underachievement correction activities were implemented from analysis of each studentÂ’s needs. Thus, combined with other student data such as test scores and grades, a strong, empirical basis for interventions would be evid ent. And finally, following inte rvention, a school counselor could show how it worked by using a similar, post-inte rvention data set of test scores, grades, and survey results.
41 Summary The literature reviewed in this chapter indicates that there are many facets of underachievement that need to be explored furt her. There is not one agreed upon definition of underachievement and researchers use different ways to identify students who underachieve. However, it is evident that th ere are many students who underachie ve. Some of these students may overcome underachievement on their own, but mo st will not. In the past, school counselors and other researchers have attempted to fi nd ways to reverse studentsÂ’ patterns of underachievement. While some of these efforts were moderately successful, most ignored an important consideration: the re searchers did not delve into r easons why the student might be underachieving but they merely pl aced students into a generic intervention plan. Contemporary theorists and researchers hold that various types of underachieving st udents exist. Therefore, an efficient and psychometrically sound method is need ed to differentiate am ong different types of underachievers. This research is in tended to develop such a measure.
42 CHAPTER 3 METHODOLOGY The School Achievement and Motivation Scales (SAMS) was developed by Amatea and Skinner (2006) to obtain information about a studen tÂ’s traits, attitudes, an d beliefs in regard to academic achievement. Although the SAMS has been subject to some professional scrutiny, it is in need of further development to facilitate understanding of both what it measures and how it performs as a measurement tool. Therefore, th e primary purpose of this study was to generate further information about the psychometric properties of the SAMS. The research procedures are presented in th is chapter, as are the sampling procedures. Also included is presentation of the previous a nd further development of the SAMS. Finally, the methodological limitations are presented. This study is descriptive in nature because student attitude, belief, and value data in regard to school achievement are collected only as bases from which to evaluate the SAMS; no experimental manipulation of variables is enco mpassed by the study. The data collected were used to evaluate the SAMS as a measure of under achievement as this term has been supported in the professional litera ture (e.g., Bleuer & Walz, 2002; Ma ndel & Marcus, 1995; Peters, 2000; Rimm, l995; Spevak & Karinch, 2000). Population The population for this study was students in gr ades six through nine in the United States. Respondents included students ag es 11 to 15 years who were proficient in use of the English language (i.e., students for whom English is a second language and/or students with other impairments to use of the English language were not be included in the sampling procedures). In addition, students who had disabilities that prohibited them from responding to the SAMS as intended were excluded.
43 The population for the study approximated th e general population of junior high school students in the United States (U.S.). According to data from the U.S. Census Bureau, there were approximately 16,689,000 sixth through ninth grade students in the U.S. in 2006. Approximate 2006 enrollments for those students by grade level were 4,050,000 for the sixth grade, 4,095,000 for the seventh grade, 4,219,000 for the eighth grade, and 4,325,000 for the ninth grade. Among those students, approximately 51.1 % were male and 48.9% were female. Approximate racial percentages for those students were 59.2% Caucasian, 15.7% African-A merican, 19% Hispanic, 3.8% Asian American, and 2.3% other racial identities (U.S. Census Bureau, 2006). Sampling Procedures The sampling for this study involved two levels. The first level encompassed the identification, recruitment, and enlistment of pr acticing school counselors. A practicing school counselor was defined here as a state-certified school counselor who was currently employed in and by a public school system. A variety of proc edures were used to engage practicing school counselors to distribute and retr ieve the SAMS from selected middle and high school students. A standardized communication (i.e ., letter) of invitation to assi st with the study (Appendix A) was distributed to enlist sc hool counselor participation. One method of distribution of the invitation to participat e was incorporation of the communication into the body (i.e., main text) of an e-mail sent individually to school counselors. The school counselors who received this method of invitation were selected from the American School Counselor Association (ASCA) national memb ership directory. This directory contained the names and e-mail addresses of all (the then) ASCA members th roughout the U.S. who allowed this information to be presented in the ASCA Directory. Specifically, all ACSA members in the Directory who identified themse lves as currently working in a middle or high school were sent an indivi dual e-mail of invitation.
44 A second method of participation soli citation was posting of the invitation communication on listservs whose memberships were likely to contain large numbers of school counselors. For example, the communicati on was posted on the School Counselor Network (SCN) listserv and the Schoolcounseling.com listserv. The third method used to solicit school c ounselor participation was correspondence with an officer of the ASCA state-level organizati ons. In general, this correspondence (which included the invitation communicat ion) was sent to the current president and/or executive director of ASCA state-level or ganizations. They were asked to (a) provide e-mail addresses of school counselor colleague s who might be willing to assist, and/or (b) distri bute the invitation correspondence electronically to members of thei r ASCA state-level orga nization (if possible), and/or (c) use any other means available to them to distribute the in vitation communication (e.g., timely publication in a statelevel ASCA newsletter). The invitation communication al so was distributed electroni cally to school counselor educators through posting on listservs to which they were likely to subscribe. For example, the invitation was posted on CESNET-L which ha d a subscription base of approximately 1400 counselor educators. The sec ond level of sampling encompassed identification, recruitment, and enlistment of students to comple te the SAMS. Convenience sampling procedures was used to select student participants for this study. That is, students in the school counselorÂ’s school were selected from among those who were willing to participate and whose parents were willing to allow them to participate. The participating sc hool counselors were asked to (a) identify middle and high school students who meet the criteria for this study (Appendix B), (b) distribute and retrieve an informed consent form (Appendix C) to the parents of the students thus identified, (c)
45 administer the SAMS to students for whom parent al informed consent has been retrieved, and (d) return the completed SAMS forms to the researcher. When potential student participants were iden tified, survey administrators were asked if they were willing to complete the SAMS. Ad ministrators were given the freedom to offer whatever incentive they felt was appropriate to encourage partic ipation. For example, some teachers offered a small amount of extra credit for the students and others offered candy. The students who indicated willingness to complete the SAMS were then informed that they had to take home an informed consent sheet home to be signed by a parent or guardian. The administrator retained a copy of the informed c onsent forms sent to parents or guardians. Upon completion of the actual sampling procedures, a su mmary description of st udent participants was compiled (Gay & Airasian, 2000). The question of needed sample size for th is study was challenging. Gay and Airasian (2000) proposed that for a population beyond 5,000, a sample size of 400 is sufficient. Other researchers recommended that for populations exceeding 10,000, a sample size between 200 and 1,000 is adequate (Alreck & Settle, 1995). Ther efore, because the greatest possible degree of generalizability was desired, a minimum of 300 participants was sought for this study. Instrumentation Essential but initial steps for development of the SAMS had been completed. The first version of the SAMS was comprised of 156 items cr eated and/or selected so as to represent 10 different constructs: Peer Achievement E xpectations/ Values, Family Achievement Expectations/Values, Student Achievement Exp ectations/Values, Student Commitment, SelfManagement Skills, Self-Confidence/SelfEfficacy, Personal Well Being, Interpersonal Diplomacy, Independence/ Depende nce, and Academic Change Readiness. The SAMS was developed to reflect the typol ogies of Mandel and Marcus (1995), Rimm (1995), Spevak and
46 Karinch (2000), and Peters (2000). The theory of change presented by Prochaska, Norcross and DiClemente (1994) also was considered in deve lopment of SAMS items. The initial set of 156 items was divided equally to create two versions of the SAMS, forms A and B. The SAMS item response format is a fiveÂ–point Likert-type set of choices: (a) Always True, (b) Mostly True, (c) Sometimes True/Sometimes False, (d) Mostly False, (e) Always False. These response choices were weighted one to fi ve for Â“directÂ” scoring and five to one for Â“reverseÂ” scoring. Seventy-six of the items we re reverse scored. Thus, a higher item score indicated a greater degree of problem for the respondent. The first three constructs in the perspec tive on underachievement underlying this study reflected perceptions of expectations. The first construct, Â“Peer Achievement Expectations/Values Â” represented respondentsÂ’ perceptions of how much their peers/friends value being successful in school. The second cons truct reflected the res pondentÂ’s perceptions of her/his familyÂ’s expectations for achieve ment, and was titled Â“Family Achievement Expectations/Values.Â” Specifically, this dimension reflected a responde ntÂ’s perception of how important it was to his/her parents/family for th e respondent to be successful in school, how the studentÂ’s school achievement or success was relate d to future life goals, and to what extent family members enforced standards of academic pe rformance in line with those goals. The third construct, Â“Student Achievement Expectations/Values,Â” represented the importance respondents placed on being successful in schoo l and how much they believed that their school achievement or success was related to their future life goals. The fourth construct refl ected respondentsÂ’ motivati on and commitment to being successful in school. In particular, the Â“Student CommitmentÂ” construct represented the degree to which the respondent was willing to work ha rd, invest time and effort to keep up with
47 assignments and school work, and follow-through. The fifth and sixth co nstructs, respectively, related to how well prepared and/or able a student was to succeed in school. The Â“SelfManagement SkillsÂ” (fifth) construct reflected how respondents viewed their knowledge of skills that helped them organize and follow-through to complete school work. The sixth construct, Â“Self-Confidence/Self-Efficacy,Â” re presented the respondentÂ’s pers onal ability confidence, an essential component academic success. The seventh construct, Â“Personal Well Be ing,Â” reflected the re spondentÂ’s level of happiness with his/her life, self, and friends because students who experienced sadness on a regular basis would have difficulty focusing on school. The eighth construct, Â“Interpersonal Diplomacy,Â” represented how well the student coope rates with others based on the idea that a student who relies on others to help them co mplete schoolwork would struggle when his/her support was not available. The ninth constr uct, Â“Independence/Dependence,Â” reflected how independently a student operated and whet her s/he could manage on his/her own. The last construct represented student re spondentÂ’s readiness to consider changing underachieving behaviors, and was ti tled Â“Academic Change Readiness.Â” A pilot test for the first version of the SAMS was conducted with 209 seventh and eighth grade students enrolled in a KindergartenÂ–grade 12 school op erated by a university. One hundred six students took the SAMS form A and 103 took the SAMS form B. The surveys were distributed so that every other pa rticipant received a different versi on of the survey. Analysis of an item response frequency dist ribution determined which item s were retained for SAMS. A SAMS item sort also was conducted with and by three practicing and state-credentialed school counselors and one school counselor educator to analyze how well item each fit into its assigned (construct) category. The selection criterion was that if at least two of these
48 professionals believed there was a strong or medium association between the item and the construct category, the item was retained. If more than two believed there was little or no association, the item was discarded. After completion of these initial procedur es, 95 items representing nine constructs remained. These nine construc ts include: Student Achievement Expectations/Values, Student Commitment, Self-Management Skills, Self-C onfidence/Self-Efficacy, Personal Well Being, Interpersonal Diplomacy, Independence/Depe ndence, Mood Management, and Academic Change Readiness. Two of the original construct categor ies (Peer Achievement Expectations and Family Achievement Expectations) were deleted and a new construct category, Mood Management, was created based on the comments of the professionals in the field who completed the item sort. Therefore in addition to the 95 questions, 16 questions were added to fulfill the need for the Mood Management factor. These changes resulted in reconfiguration of items based on the item sort and professional revi ews, and resulted in the SAMS being composed of 111 items (Appendix D). Data Collection Procedures Each participating school counselor recei ved explicit, written SAMS administration instructions (Appendix E). Part icipating school counselors admini stered the SAMS to students individually or in small groups. Upon completion of the administration of the SAMS to students, the participating schoo l counselors mailed the completed informed consent forms and the participantsÂ’ test scores and school grades to the researcher. The SAMS was made available to participa ting student respondents through the internet. The survey administrator was given directions fo r administering the SAMS online (Appendix E). An important part of these directions was that the school counselor must convey to the students that the students were not being Â“evaluatedÂ” ba sed on their responses. The students also were
49 informed that their responses would be kept confidential within limits allowed by law. The school counselor administrators sign ed a letter of confiden tiality in which they agreed not to look at studentsÂ’ SAMS responses and to ensure th e confidentiality of each participant (Appendix F). Each participating student provided their student identification number on the survey because the school counselor was asked to provide studentsÂ’ grade point average and standardized test scores for each student identification number. The survey administrator had each student co mplete the SAMS online. The administrator mailed all corresponding student sc hool data sheets and informed consent forms in a separate pre-addressed, stamped envelope and mailed them to the researcher after all participating students had provide d their responses. Research Questions The following research questions were examined in this study. The applicable statistical analyses used to address the re spective questions are presented. RQ1: What is the factor st ructure of the SAMS? A principal components factor analysis was cond ucted to address the first research question. Both orthagonal (varimax) and oblique (promax) ro tations were applied. These analyses were to allow determination of subscale st ructure (if any) for the SAMS. RQ2: To what extent does the determined f actor structure confirm the proposed, theoretical structure? The factor structure derived for the first rese arch question was examined in relation to the proposed theoretical structure. RQ3: What are the reliability coefficients for each of the SAMSÂ’ subscales? Coefficient alphas were calculated for each of the resultant SAMSÂ’ subscales. RQ4: What are the age group or gender differences in SAMS scores?
50 Upon determination of the subscale s for the SAMS as per research question one above, subscale scores for each respondent for each SAMS subscale were computed. Differences in the means of each of the SAMS subscales were then examined by application of a factorial 2 x 4 (gender by grade level) analysis of variance. The level of statis tical significance for each analysis was .05. A Newman-Keuls post hoc analysis was applie d to determine the pa ttern of significant differences among the means. RQ5: What are the relationships between su bscale scores on the SAMS and student achievement? Subscale scores were computed fo r the participants whose school data were available. These studentsÂ’ scores on each scale we re correlated with their grade poi nt averages, their grades in language arts and math, and their standardized te st scores on reading and math. A significance level of .05 was used to test for significant rela tionships between studentsÂ’ scores on a specific subscale and their grades, grade poi nt averages, or test scores. Methodological Limitations The primary methodological limitation for th is study was the participating students had no direct motivation to respond to the SAMS ope nly, honestly, or completely. Students may have agreed to particip ate solely to receive th e incentive offered by the survey administrator. Therefore, there was no way to determine whet her the students responded to the questions honestly and accurately. In addi tion, the participants likely had relatively low motivations to perform fully on school-based assessments. Ho wever, presumably, prac ticing school counselors and teachers were adept at motivating students to respond appropriately and fully to a particular assessment, and particularly when the intention was to use the resultant information to help students like them. Therefore, they should have been able to motivate students to respond appropriately. In addition, the requirement for parental permission for pa rticipation necessarily
51 meant that parents would have to have been awar e of their childrenÂ’s par ticipation and may have served to motivate their child ren to respond appropriately. A similar limitation applies to the participa ting school counselors and teachers. That is, they too did not have any direct incentive to assist with the study. However, most practicing school counselors and teachers, as dedicated professionals, rec ognize the need for and value of substantive research that has good potential fo r application in the education profession. Therefore, it was likely that the educators who agr eed to participate did so to the best of their respective abilities.
52 CHAPTER 4 RESULTS The purpose of this study was to examine various underachievement typologies through further development of the School Achievement and Motivation Scales (SAMS). The SAMS was derived from a conglomeration of typology theori es. The psychometric properties of the SAMS and of factors associated with responding to it were investigat ed through analyses of studentsÂ’ responses. The results of this i nvestigation are presented in this chapter. A discussion of the psychometric properties, data analys es, and responses to each research question also is presented. Finally, the results of analyses of responses potentially differentiated by selected respondent characteristics are presented. Sample Demographics A total of 388 student res pondents completed the SAMS onlin e. The respondents were in grades six through nine, fluent in English, and did not have a lear ning disability. All respondents lived in either Florida or Minne sota in the United States. The schools located in Minnesota were both in suburban settings, one wa s public (grades 6-8) and one wa s private (grades K-8). Nine Florida schools participated including four suburban middle schools, one suburban high school, one urban high school, and one unive rsity school (grades K-12). Participants ranged in age from 11 to 15 years and had an average age of 13.22 (s.d. = 1.18) years. The median age of the particip ants was 13 years. Among the participants, approximately 217 were female and 169 were male. Ninety-two of the participants were in 6th grade, 133 in 7th grade, 54 in 8th grade, and 107 were in 9th grade (see Table 4-1). Two of the participants did not repo rt their grade level or their gender. Of the re spondents, 315 were from Florida and the remaining 73 were from Minnesota.
53 In schools in which testing a nd grade data were available, a school counselor or teacher assisted with the research by providing each studen t participantÂ’s most recent standardized test data, grade point average, and grades in Language Arts and Mathematics. Of the 388 participants, 328 studentsÂ’ grades and/or test scores were reported. For these 328 respondents, their average reading percentile was 85.43 and their average mathema tics percentile was 84.90. Their average grade poin t average was 3.25 on a 4.0 scale. Si milarly, their average grade point average in Language Arts was a 3.13 and their aver age grade in Math was 3.07 (see Table 4-2). Research Questions The first research question for the study was: What is the factor structure of the SAMS? The 111 items on the SAMS were analyzed us ing a principal components analysis (PCA) to determine its factor structure. The PCA fo r these 111 items yielded 23 factors in the initial (i.e., unrotated) factor structure of the SAMS. The majority of the items (n=90) loaded on the first factor (using a minimum factor loading of .40). Eight items loaded on the second factor and the remaining 21 factors contained between one and three items. A sc ree plot was used to further examine how many factors should be retained. Th e scree plot showed a substantial drop in the respective eigenvalues of the compon ent factors after five factors. Therefore, based on the scree plot, five factors were re tained. Presented in Table 4-3 are th e factor loadings of each of the 111 items for the five factor (unrotated) PCA solution. The initial factor structure demonstrated in ter-factor correlations ranging from .216 to .605, which suggested that the angl es between factors were quite large in general and thus uncorrelated. Therefore, it was determined that an orthogonal solution was the most appropriate method of rotation to determine the final factor structure. Specifically, the varimax rotation method was applied.
54 Shown in Table 4-4 are the results of the va rimax rotation on the 111 items. Subsequently, items that did not have at least a .40 loading on at least one factor or th at had a .30 or greater loading on more than one factor were eliminated. The results of application of these criteria are shown in Table 4-5. It can be seen that a total of 62 items remained. This is the factor structure upon which subsequent analyses were based. These five factors were identified (i.e., named) as (I) Dedication to Schoolwork, (II) Personal Well -Being, (III) Interpersonal Diplomacy, (IV) Desire to Learn and Succeed, and (V) Academic Self-Concept. Each of the five factors shown in Table 45 was treated as a subs cale of the SAMS, and each retained survey item was assigned to one of the five subscales based on highest factor loading. Subscale scores for each respondent then were computed by summing the response weights for each item for each particular subscale. Alpha coefficients were then computed to establish the reliability coefficients for each subscale (see Table 4-5). Note that for this analysis, the scoring of the negative items was reversed. The positive SAMS items were scored as Not at all like me = 1), Not very much like me = 2), Somewhat like me = 3), Much like me = 4), and Very much like me= 5). The negative items were reverse scored Not at all like me = 5), Not very much like me = 4), Somewhat like me = 3), Much like me = 2), and Very much like me= 1). The second research question was: To what extent does the determined factor structure confirm the proposed, theoretical structure? The questions chosen for the su rvey originally were derive d from several theories of underachievement typologies. Subsequently, th e original set of items on the SAMS was examined in a pilot study which helped to narrow the construct list to nine components: Student Achievement Expectations/Values, Student Commitment, Self-Management Skills, Self
55 Confidence/Self-Efficacy, Personal Well Being, Interpersonal Diplomacy, Independence/ Dependence, Academic Change Readiness, and Mood Management. The SAMS that emerged from the final fact or structure included 62 items over five subscales (Table 4-6). The five subscales were similar, but not identical, to the nine components upon which the original SAMS was based. All of the nine components of the original SAMS were represented; however, they were organized differently. Some of the originally proposed constructs merged into one subscale. For ex ample, Student Commitment and Self-Management Skills emerged as part of the first subscale. Comparison of the proposed and derived constructs and SAMS subscales are discussed following. Dedication to Schoolwork The first derived subscale consisted of items that predominantly came from the two proposed constructs of Student Commitment and Self-Management Skills. It also included some items from the Change Readiness construct, but the new subscale included only the Change Readiness items that indicated the student wa s already actively involved in improving her/his school behaviors. This subscale represents th e importance participants placed on learning and working hard in school. Items from this subscale include I am well organized I am actually doing something to improve how I study for tests and I keep track of when my school assignments are due Similarly, reverse scored ite ms for this subscale include I forget to do homework assignments and I come to class unprepared This subscale consisted of 14 items with factor loadings ranging from .477 to .715. The mean for this subscale was 50.32, with a standard deviation of 10.89.
56 Personal Well Being The second subscaleÂ’s items came predominantly from the original constructs of Personal Well Being and Mood Management. There were a very few items from some of the other original scales represented, but all of the items focused on the studentÂ’s happiness with his/herself and life in general. This subscale reflects whether partic ipants experienced feelings of sadness, anxiety, stress, and whether they felt like they belonged. A student who is highly depressed, anxious, and/or cannot de al with stress effectively woul d score low on this subscale. Sample items included I am a happy person I feel like I belong and I can handle the stresses and pressures of school Reverse scored items included I get depressed easily I do not feel good about who I am and I have trouble falling asl eep or staying asleep This subscale consisted of 18 items with factor loadings ranging from .424 to .700. The mean for this subscale was 70.12, with a standard deviation of 11.91. One original item, I work well with others did not fit well into this subscale, although to some degree it did relate to whether a stude nt feels like he/she belongs. Interpersonal Diplomacy The subscale of Interpersonal Diplomacy repr esented studentsÂ’ relationships with those around them. Students who cooperate well with others would score high on this subscale, whereas those who did not cooperate effectively with others would score low. Most of the items on this subscale came from the original c onstructs of Interpersonal Diplomacy and Independence/Dependence. All items on this subscale were reverse scored. Sample items included Adults think I have an Â“attitudeÂ” problem I like to get my way even if it makes others upset and I tell people off if they get on my nerves Three of the items within this subscale did not fit well with the concept of Â“Interpersonal Diplomacy.Â” Ho wever, they all indicated a
57 negative attitude toward school a nd a lack of willingness to change their behavior. All of these items came from the original Change R eadiness construct. An example is As far as I am concerned, how I do in school is no oneÂ’s business but my own The Interpersonal Diplomacy subscale consisted of 11 items with factor load ings ranging from .410 to .566. The mean for this subscale was 36.80, with a standard deviation of 8.02. Desire to Learn and Succeed The fourth subscale, identified as Desire to Learn and Succee d, reflected how participants felt about school success. Students who would sc ore high on this subscale believe school is important for their future. Conversely, students with a low Desire to Learn and Succeed do not see the value of doing well in school Most of the items on this s ubscale came from the original constructs of Student Achievement Expectati ons/Values and Self-Management Skills. Sample items included I plan for my future and I love learning new things The two reverse scored items were ItÂ’s a waste of time to plan for my future and It is just not that impor tant to me to do well in school Two items did not fit well into this subscale: I am a capable person and I think I might be ready to work at trying to get better grades The Desire to Learn and Succeed subscale consisted of 10 items with factor loadings ranging from .426 to .599. The mean for this subscale was 41.77, with a standard deviation of 5.37. Academic Self-Concept The fifth and final subscale was comprised of items that reflected whether a student had high confidence in his/her academic abilities. Approximately half of the items referred to whether the student felt the need for more assistance in school a nd the other half contained items that indicated a studentsÂ’ level of anxiety in relation to school. Therefore, students who would score low on this subscale have low self-conf idence and high anxiety in relation to their
58 academic abilities. The items on this subscale were primarily from the original constructs of Self-Confidence/Self-Efficacy, Mood Management and Change Readiness. The Change Readiness items all indicated that a student felt the need for extra assistance in school. All of the items from the Academic Self-Concept subscale were reverse scored. Sample items included I get so nervous when I take a test that I donÂ’t do as well as I should and I need help figuring out how to do my school assignments The Academic Self-Concept s ubscale consisted of 9 items with factor loadings ranging from .462 and .733. The mean for this subscale was 33.09, with a standard deviation of 7.24. The third research question was: What are th e reliability coefficients for each of the SAMSÂ’ subscales? CronbachÂ’s alpha coefficients were computed for each of the five subscales and are shown in Table 4-5. The lowest reliability coeffi cient was .788, indicating th at each subscale was highly reliable. The overall CronbachÂ’s alpha fo r the SAMS was .937, which again is substantial for an instrument of this nature. The fourth research question was: What are the age group (grade level) or gender differences in SAMS scores? The participantsÂ’ response data were categorized into grad e level by gender categories. Examination for statistically significant differe nces among the means by grade level or between the means by gender for each of the respective s ubscale scores was achieved by computing a 4 x 2 (age group [grade] by gender) factorial analysis of variance (ANOVA). The alpha level was set at .05 for these calculations. The means and st andard deviations for these analyses are shown in Table 4-7 and the results of the relate d data analyses are shown in Table 4-8.
59 It can be seen in Table 4-8 that most of th e main effect F values were not statistically significant. However, there was a statistically significant F value for grade level for subscale one, Dedication to Schoolwork. S ubsequently, the Newman-Keuls post hoc comparison revealed that the grade 6 and 7 means were not statistically significant from each other. Similarly, grades 8 and 9 were not statistically significant from each other. However, subscale one means for grades 6 and 7 were significantl y different from subscale one mean s for grades 8 and 9 (and vice versa). Inspection of the means for each grade level indicated that the 6th and 7th grade means were higher than the 8th and 9th grade means on the first subscale. There was also a statistically significant F valu e for subscale five, Academic Self-Concept. Subsequently, the Newman-Keuls post hoc comparison revealed that th e statistically significant difference between grade levels on subscale five was between grade 6 and grades 7 and 9. That is, the grade 6 mean was statistically significan tly different from both the grade 7 and grade 9 means, and the 6th grade mean was significantly higher th an grade 7 and 9 means for the fifth subscale. Four of the subscales did not yield statistic ally significant intera ction effects between grade level and gender. However, the fourth subscale, Desire to Learn and Succeed, yielded a statistically significant intera ction effect [F (3,378) = 2.78, p = .04]. The fifth research question was: What are the relationships between subscale scores on the SAMS and student achievement? Subscale scores were computed for the student participants and these subscale scores were compared to the studentsÂ’ school da ta for those students for whom such data were available. Of the 388 participants, standardized test scores we re available for 328 students, math and language arts grades were available for 284 students, and cumulative grade point average data were
60 available for 347 students. For those for whom it was possible, the studentsÂ’ scores on each subscale were correlated with their grade point averages, grades in language arts and math, and standardized test scores in r eading and math. Shown in Tabl e 4-9 are the Pearson correlation coefficients for studentsÂ’ subs cale scores and school data. On subscale one, Dedication to Schoolwork, stude ntsÂ’ scores were positively correlated with their Mathematics test scores, grades in Language Arts and Mathematics, and cumulative grade point averages (GPA). Subscale two, Pe rsonal Well-Being, was positively correlated with studentsÂ’ grades in Language Arts and Mathem atics and GPA. Interpersonal Diplomacy, the third subscale, was positively correlated with Ma thematics and Reading test scores, Mathematics and Language Arts grades, and GPA. The fourth subscale, Desire to Learn and Succeed, was positively correlated with studentsÂ’ Reading test scores, Language Arts and Mathematics grades, and GPA. Academic Self-Concept was positively co rrelated with Reading and Mathematics test scores, Language Arts and Mathematics grades, and GPA.
61 Table 4-1. Respondent characteri stics by gender and grade level Grade level Male Female Total Sixth 48 44 92 Seventh 61 72 133 Eighth 26 28 54 Ninth 34 73 107 Total 169 217 386
62 Table 4-2. Means for respondent national norm percentiles for Mathematics and Language (English) standardized test scores and means for Mathematics and Language Arts grades Variables N Mean Standardized Test Scores* Mathematics 328 84.90 Reading 328 85.43 Current Subject Grade** Mathematics 284 3.07 Language Arts 284 3.13 Overall Grade Point Average 347 3.25 Standardized test scores are the stud entsÂ’ percentages based on national norms. ** Grades reported based on a 4.0 grading scale (A=4.0; B=3.0; C=2.0; D=1.0; F=0.0).
63 Table 4-3. SAMS factor loadings following the initial principal components factor analysis Item Factor 1 Factor 2Factor 3Factor 4 Factor 5 65 -.701 .125 .191 .250 .004 25 -.696 .038 .016 .299 .165 46 .680 -.115 .186 -.257 -.274 10 -.676 .221 -.008 .190 .272 61 -.673 .119 .023 .157 .270 88 .673 .076 -.071 -.041 .000 34 .670 -.051 .134 -.139 .058 50 -.667 .225 .036 .177 .095 64 -.666 .090 .029 .305 .170 43 .649 -.097 .115 -.120 -.313 90 -.648 -.256 .315 .068 .066 24 -.642 .035 .051 .200 .023 53 .641 -.159 .172 .059 -.181 74 -.625 .095 .126 -.048 .068 31 .622 -.139 .197 -.014 -.209 96 .617 -.209 .186 -.025 .152 111 -.614 .260 -.059 -.020 .290 110 -.609 .207 .162 .064 .237 99 .604 -.149 .048 -.091 -.066 22 .603 .201 .140 -.100 .148 72 .601 -.077 .252 -.258 .037 85 -.592 .136 .086 .030 .338 94 -.588 .235 -.025 -.113 .317 77 -.581 -.263 .098 .051 .289 18 -.576 -.013 .330 .082 .013 102 .570 .129 .135 .255 .064 109 .567 .252 -.123 .166 .033 69 -.566 -.085 .287 .057 .002 42 .564 .237 .145 .128 -.098 63 .560 -.289 .130 .038 .371 56 -.550 .389 -.124 .078 .104 93 -.549 -.257 .232 -.368 .140 68 .548 -.161 .297 .157 -.145 54 -.547 -.241 .112 .071 .242 27 .543 -.140 .137 .137 .088 4 -.543 -.103 .175 .090 -.119 66 .542 -.119 .293 .207 -.166 11 -.534 -.336 .087 .113 .222 107 .528 .085 .000 -.001 -.106 73 .524 -.110 -.039 -.075 .229 44 -.523 .380 -.160 .188 .062 58 -.522 -.291 .197 .047 -.032 86 -.520 .213 .256 .062 -.193 70 .519 -.290 .313 -.269 -.003
64 Table 4-3. Continued Item Factor 1 Factor 2Factor 3Factor 4 Factor 5 51 .519 -.362 .207 .124 .176 41 -.518 .299 .149 -.043 .286 60 .518 .051 .335 .050 -.003 17 .516 .142 .009 .236 .134 48 .510 .366 -.106 .350 .139 89 .509 -.411 .124 .111 .157 21 -.509 .337 .115 -.030 -.211 19 -.508 .306 -.040 -.058 .247 79 .504 .396 -.110 .339 -.040 28 .500 .327 .005 .370 .005 81 .495 .315 .129 -.319 .005 92 -.482 -.012 .328 .111 -.034 12 .482 -.017 .112 -.125 .058 20 .481 .171 .130 .243 .041 38 -.473 -.088 .201 .135 -.014 40 .468 .216 .135 .131 -.042 95 .463 .107 .259 .076 .128 23 .460 -.157 .337 .136 .018 2 -.459 .072 .036 .109 .055 101 .454 -.385 .189 .072 .198 78 .453 .304 -.036 -.188 .237 83 .451 .148 .189 .160 .121 82 -.448 .301 .035 .037 .187 1 -.440 .215 .164 .058 -.193 100 .425 -.080 -.273 -.078 .362 29 -.420 -.069 .181 -.145 -.020 5 -.418 -.207 .033 .383 -.187 7 -.410 -.346 .223 -.149 .145 9 .405 -.119 .300 .239 -.036 32 -.400 -.028 .195 -.045 .101 84 -.397 -.332 .237 -.287 .201 98 -.393 .371 .153 -.233 .264 104 -.392 -.238 .135 -.335 .138 76 .384 .321 .074 .270 -.064 105 .382 .331 .005 .323 -.005 49 .374 -.006 .320 .316 -.039 33 .370 -.224 .268 .076 .218 87 -.366 -.110 .196 -.201 .146 91 .361 .295 .247 -.125 .118 97 .360 -.020 -.114 .081 .105 80 -.342 -.226 .301 -.128 -.019 30 .333 -.138 .319 .116 .027 103 .305 -.066 .226 .162 .136 106 .295 -.134 .209 .102 -.009
65 Table 4-3. Continued Item Factor 1 Factor 2Factor 3Factor 4 Factor 5 62 .267 .109 -.054 .130 .031 15 .242 .070 -.102 -.203 .172 35 .096 .563 .106 -.218 .220 39 .294 .515 .250 -.394 -.070 45 .287 .505 .209 -.448 -.103 13 -.106 .494 .249 -.350 -.224 16 .252 .486 .090 -.161 .167 6 .199 .440 -.036 .114 -.020 55 .400 .428 .192 -.331 -.065 52 .334 .402 .171 .179 -.117 67 .332 .372 .184 -.155 .045 59 .209 .328 .258 .102 .134 8 .147 .326 .281 -.214 .203 75 -.279 .263 .426 .148 -.230 57 -.357 .209 .393 .100 -.144 71 .330 .006 .390 .253 -.025 108 .000 -.132 .366 -.120 .020 47 .015 -.035 .341 .236 .052 36 -.149 -.059 .300 .036 .260 26 -.245 .275 .298 -.184 -.243 37 .280 .234 -.050 .302 .023 14 -.252 .086 .194 .069 -.273 3 .243 -.054 -.093 -.065 .248
66 Table 4-4. SAMS varimax rotated factor loadings Item Factor 1 Factor 2Factor 3Factor 4 Factor 5 10 .715 -.089 -.214 .198 -.110 46 -.689 .055 .292 -.098 .282 61 .672 -.175 -.176 .179 -.145 43 -.655 .157 .261 -.058 .173 85 .641 -.232 -.126 .105 -.004 111 .636 -.149 -.307 .098 .045 64 .635 -.092 -.132 .272 -.264 25 .631 -.135 -.144 .267 -.307 110 .625 -.192 -.113 .244 .029 94 .605 -.221 -.291 .058 .107 41 .599 -.163 -.134 .166 .180 50 .594 -.088 -.231 .334 -.106 65 .557 -.156 -.104 .476 -.184 19 .549 -.100 -.285 .095 .125 31 -.546 .150 .389 -.065 .116 53 -.526 .196 .418 -.093 .059 102 .519 -.082 -.074 .357 -.163 82 .507 -.037 -.185 .167 .097 99 -.480 .124 .285 -.247 .121 24 .478 -.168 -.170 .335 -.243 98 .477 -.179 -.172 .107 .373 74 .450 -.303 -.202 .295 -.016 72 -.419 -.011 .379 -.235 .353 34 -.412 .142 .365 -.303 .277 88 -.400 .345 .202 -.309 .222 4 -.398 .197 .390 -.071 .061 27 .395 -.297 -.023 .233 -.255 2 .373 -.118 -.136 .218 -.117 32 .303 -.295 -.011 .180 -.012 12 -.286 .092 .264 -.222 .235 36 .278 -.200 .254 .025 .042 93 .227 -.700 -.105 .128 .011 79 -.111 .696 .143 -.063 .136 48 -.003 .669 .208 -.191 .138 70 .165 -.661 -.015 .241 -.050 84 .200 -.636 .042 -.002 -.032 28 -.082 .633 .267 -.047 .118 44 -.110 .611 .091 -.202 .220 104 .163 -.569 -.091 .002 .015 7 .206 -.557 .065 .061 -.142 105 -.030 .554 .195 .001 .117 56 -.130 .552 .102 -.251 .320 109 -.202 .537 .157 -.222 .171 90 .398 -.505 .064 .333 -.256
67 Table 4-4. Continued Item Factor 1 Factor 2Factor 3Factor 4 Factor 5 76 -.083 .501 .214 .059 .159 37 .007 .455 .137 -.031 .026 80 .108 -.454 .082 .218 -.055 52 -.079 .445 .194 .166 .281 17 -.106 .439 .313 -.217 .102 58 .231 -.434 .007 .275 -.288 87 .239 -.425 -.019 .079 .045 6 .041 .424 -.024 .052 .252 20 -.124 .415 .356 -.071 .137 40 -.189 .374 .278 -.019 .221 29 .191 -.372 -.089 .231 -.004 62 -.071 .274 .102 -.104 .046 108 -.034 -.265 .264 .104 .116 51 -.261 .019 .566 -.307 -.082 23 -.248 .090 .542 -.054 .052 63 -.168 .034 .531 -.496 .029 18 -.294 .198 .528 -.080 .206 101 -.232 -.052 .518 -.320 -.085 71 -.106 .182 .511 .124 .066 89 -.295 .006 .504 -.346 -.140 9 -.211 .166 .504 .021 -.021 33 -.107 -.022 .503 -.217 .025 49 -.132 .257 .502 .092 .004 69 -.327 .150 .498 -.112 .154 77 -.224 .084 .491 -.454 .021 96 -.332 .071 .490 -.335 .123 11 -.250 .071 .489 -.402 -.088 54 -.220 .093 .474 -.390 .012 60 -.255 .187 .472 -.030 .251 30 -.167 .037 .463 -.015 .038 95 -.116 .221 .422 -.113 .249 103 -.049 .112 .410 -.094 .033 83 -.081 .312 .384 -.108 .196 47 .121 .029 .381 .177 -.053 106 -.180 .052 .351 -.029 -.003 100 -.090 .151 .074 -.599 .060 75 .183 .000 .112 .584 .125 86 .298 -.139 -.125 .548 .029 57 .252 -.093 .075 .519 .099 66 .266 -.267 .044 .502 -.264 21 .279 -.071 -.294 .497 .118 68 .255 -.326 .043 .470 -.259 42 .404 -.080 -.182 .468 -.032 1 .240 -.075 -.159 .468 .022
68 Table 4-4. Continued Item Factor 1 Factor 2Factor 3Factor 4 Factor 5 26 .049 -.135 -.095 .446 .298 73 -.229 .121 .263 -.444 .128 14 .037 -.059 -.038 .426 -.021 92 .326 -.260 .067 .410 -.091 3 -.028 .046 .094 -.346 .069 107 .280 -.183 -.282 .321 -.095 38 .305 -.246 .012 .315 -.093 15 -.079 .044 -.017 -.296 .220 97 -.141 .226 .135 -.268 .002 45 -.191 .094 -.052 .083 .733 39 -.150 .120 .006 .092 .727 55 -.226 .173 .057 .006 .641 35 .216 .180 -.054 -.041 .591 81 -.275 .172 .106 -.139 .571 13 -.004 -.032 -.186 .370 .562 16 .077 .251 .028 -.085 .533 8 .113 .017 .156 -.026 .506 67 -.079 .207 .132 -.020 .492 5 .177 -.070 -.010 .352 -.490 91 -.059 .168 .242 -.064 .462 78 -.076 .255 .081 -.333 .449 22 -.218 .268 .310 -.259 .415 59 .121 .248 .263 .054 .312
69 Table 4-5. SAMS total and subscale summary statistics Scale Number of Items Alpha Coefficient Mean Standard Deviation Dedication to Schoolwork 14 .912 50.32 10.89 Personal Well Being 18 .895 70.12 11.91 Interpersonal Diplomacy 11 .821 36.80 8.02 Desire to Learn and Succeed 10 .788 41.77 5.37 Academic Self-Concept 9 .827 33.09 7.24 SAMS total 62 .937 232.34 31.76
70 Table 4-6. Subscale structure of SAMS Subscale 1: Dedication to Schoolwork (DS) Item 10. I keep track of when my school assignments are due. 46.* I forget to do homework assignments. 61. I remember what IÂ’m supposed to do for homework. 43.* I put off school assignments more than I should. 85. I am well organized. 64. I am up to date in completing my school assignments. 110. I am really working hard at keep ing up to date on my school assignments. 94. I set aside a certain amount of time to do schoolwork and I stick with it. 41. I am really working hard at keepi ng my school assignments and papers organized. 19. I am setting aside a certain amount of time for school work and sticking with it. 102. I work hard to get a good grad e even when I donÂ’t like a class. 82. I am spending more time working on my school assignments. 99.* I come to class unprepared. 98. I am actually doing something to improve how I study for tests. Subscale 2: Personal Well Being (PWB) Item 93. I am a happy person. 79.* I get depressed easily. 48.* I feel Â“blueÂ”. 70. I like myself. 84. I find it easy to relax. 28.* I find I am depressed for no reason at all. 44.* I do not feel good about who I am. 104. I sleep well. 7. I feel like I belong. 105.* I blame myself for things. 109.* I am easily discouraged. 76.* I hide my feelings. 37.* I have trouble falling asl eep or staying asleep. 80. I have friends I can rely upon. 52.* I worry that other people will be disappointed in me. 58. I can handle the stre sses and pressures of school. 87. I work well with others. 6.* I get so nervous I can barely function. Subscale 3: Interpersonal Diplomacy (ID) Item 51.* All this talk about doing well in school is boring. 23.* I do not like being told what to do. 18.* Adults think I have an Â“attitudeÂ” problem. 71.* I argue with people I care about. 9.* I like to get my way even if it makes others upset. 33.* The most important part of school for me is being able to talk and socialize with my classmates.
71 Table 4-6. Continued Subscale 3 (Continued) Item 49.* I am critical of others. 60.* My temper gets me in trouble. 30.* I tell people off if they get on my nerves. 95.* I get blamed for things I didnÂ’t do. 103.* As far as I am concerned, how I do in school is no oneÂ’s business but my own. Subscale 4: Desire to Learn and Succeed (DLS) Item 100.* ItÂ’s a waste of my time to plan for my future. 75. I think about what I am goi ng to do with the re st of my life. 86. Doing well in school is importa nt for my future career goals. 57. I plan for my future. 66. I am a capable person. 21. I like school. 1. I love learning new things. 26. I think I might be ready to work at trying to get better grades. 73.* It is just not that impor tant to me to do well in school. 14. My success is up to me. Subscale 5: Academic Self-Concept (ASC) Item 45.* I want someone to help me figure out how to study for tests. 39.* I wish someone could help me figure out how to study for tests. 55.* I know I need to talk with some one about how I can do better in school. 35.* I wish I had more ideas about how to be less tense when I take tests. 81.* I need help figuring out how to do my school assignments. 16.* I get so nervous when I take a te st that I donÂ’t do as well as I should. 8.* I have been getting help from people (e .g. tutoring, counseling, coachi ng) to improve my grades. 67.* I worry that I will get failing grades. 91.* I get very tense when I study. Reversed items.
72 Table 4-7. Subscale means and standard deviations for grade level and gender Subscale 1: Dedication to Schoolwork 6th Grade7th Grade 8th Grade 9th Grade Males Mean s.d. 3.86 .51 3.47 .68 3.19 .65 3.46 .74 Females Mean s.d. 3.87 .63 3.81 .83 3.45 .88 3.40 .88 Subscale 2: Personal Well Being 6th Grade7th Grade 8th Grade 9th Grade Males Mean s.d. 3.97 .59 3.83 .58 3.71 .73 3.86 .59 Females Mean s.d. 4.10 .66 3.96 .70 3.90 .67 3.78 .68 Subscale 3: Interpersonal Diplomacy 6th Grade7th Grade 8th Grade 9th Grade Males Mean s.d. 3.46 .45 3.26 .73 3.18 .63 3.36 .66 Females Mean s.d. 3.55 .65 3.44 .82 3.25 .92 3.21 .78 Subscale 4: Desire to Learn and Succeed 6th Grade7th Grade 8th Grade 9th Grade Males Mean s.d. 4.10 .56 4.15 .48 3.72 .63 4.15 .57 Females Mean s.d. 4.27 .50 4.29 .49 4.28 .45 4.21 .53 Subscale 5: Academic Self-Concept 6th Grade7th Grade 8th Grade 9th Grade Males Mean s.d. 3.91 .68 3.56 .87 3.89 .72 3.48 .81 Females Mean s.d. 3.99 .67 3.67 .86 3.59 .74 3.46 .83
73 Table 4-8. Four by two (grade le vel by gender) factorial analysis of variance for subscale scores Subscale 1: Dedication to Schoolwork Source SSdfMS F p Grade Level (GL) 13.35 34.457.91 .00* Gender (G) 1.57 11.572.79 .10 GL x G 2.78 3 .931.65 .18 Error 212.76378 .56 Subscale 2: Personal Well Being Source SSdfMS F p Grade Level (GL) 2.79 3.932.20 .09 Gender (G) .71 1.711.68 .20 GL x G .87 3.29 .69 .56 Error 159.83378.42 Subscale 3: Interpersonal Diplomacy Source SSdfMS F p Grade Level (GL) 3.38 31.132.15 .10 Gender (G) .20 1 .20 .39 .54 GL x G 1.50 3 .50 .95 .42 Error 198.54378 .53 Subscale 4: Desire to Learn and Succeed Source SSdfMS F p Grade Level (GL) 1.87 3 .62 2.27 .08 Gender (G) 4.50 14.5016.41 .00* GL x G 2.28 3 .76 2.78 .04* Error 103.67378 .27 Subscale 5: Academic Self-Concept Source SSdfMS F p Grade Level (GL) 11.55 33.856.13 .00* Gender (G) .10 1 .10 .15 .70 GL x G 1.70 3 .57 .90 .44 Error 237.64378 .63 p 0.05
74 Table 4-9. Correlations among respondent subs cale scores, grade point averages, and standardized test percentiles Reading test scores Mathematics test scores Language arts Grade Mathematics grade Grade point average Subscale 1 .094 .143** .249** .291** .411** Subscale 2 .100 .070 .177** .150* .222** Subscale 3 .124* .119* .177** .216** .276** Subscale 4 .121* .082 .135* .142* .210** Subscale 5 .162** .345** .430** .462** .461** ** p .01 p .05
75 CHAPTER FIVE DISCUSSION The purpose of this study was to facilit ate further development of the School Achievement Motivation Scales (SAMS), an asse ssment developed to assist school counselors working with underachieving students. The original SAMS items were based on the underachievement typology theories of Mandel and Marcus (1995), Rimm (1995), Spevak and Karinch (2000), and Peters (2000) in addition to the theory of change presented by Prochaska, Norcross, and DiClemente (1994). Because of its strong conceptual basis, the SAMS was promising in its original form, but lacked an em pirical basis for its psychometric properties. Therefore, the purposes of this study were to determine the psychometric properties (including its factor structure) of the SAMS and to inves tigate possible variations in response style based on selected respondent characteristics Presented in this chapter are the limit ations, discussion of the results, implications, and recommendati ons that evolved from the research. Limitations For the SAMS to be a useful resour ce for school counselors (and possibly other educational professionals), generalized applicability across students in a variety of settings would be highly desirable (Gay & Airasian, 2000). Ther efore, random selectio n of student subjects would have been the ideal. However, because of the pragmatic difficulties of obtaining student participants through a random sel ection procedure, a convenience sample was used. Therefore, there are some limitations to the generalizabil ity of the sample from which the data were obtained. For example, the participants did not repr esent students in all regi ons of the U. S. Of the 388 participants, approximately 85% came fr om Florida, including 16% who were from North and Central Florida and 69% who were fr om South Florida. The remaining 15% were
76 from Minnesota. Because most of the population came from Florida, the study is limited to the extent that the students in the sa mple do not represent students from other regions of the country. Approximately 56% of the sample was female and 44% was male, which is a good approximation of student distributio n by gender in the U.S. The pa rticipants were not asked to divulge their ethnicity, and theref ore the extent to which the sa mple was ethnically diverse is unknown. However, the regions from which the sample was selected are relatively diverse ethnically, and therefore it is likely that the participants also were ethnically diverse. Another possible limitation of this study was that the ac tual data collection was performed by different people, which may have skewed how the participants responded to the survey questions. However, the data collection always began in the school setting. Sometimes the school counselor helped with the data collect ion and in other schools, the teachers collected the data. However, in all situations, the school faculty member asked the students to volunteer to participate, and gave the student s the same directions once parent al permission to participate was obtained. Further, all data collectors were given specific instructi on in the procedural requirements for the study. Therefore, while th ere may have been some variation in responding attributable to variation in admi nistrators, it is not likely that different administrators were a strong source of differentiation in responses. Another possible limita tion is that the students were offered different incentives to part icipate in the survey. Similarly, the data collector at each site was given the choice to use an incentive. For example, in some schools a free Â“homework passÂ” or a Â“no uniformÂ” pass was offered if the student pa rticipated in the survey. Other schools chose to give the students candy after the student returned a signed in formed consent form and then took the survey online. However, although there were some differences in the participation incentives offered and/or provided, in most cases th e students participated primarily because they
77 were requested to do so. Therefor e, variations in incentive to part icipate were not likely a major source of differentia tion in responding. All the data collectors were in structed to tell the students to be as hone st as possible in responding to the survey, that thei r participation and/or results would not impact or influence their school work or status, and that their resu lts would be kept confidential. However, the participants may have responded according to how they thought their peers would respond and/or according to how they thought others (e .g., teachers or parents) would like them to respond instead of responding as genuinely as possibl e. Therefore, it is possi ble that some of the responses were not as accurate as they might have been because of social desirability effects. However, there was no suggestion or evidence of syst ematic bias in this re gard, and it is likely that social desirability was not a significant fact or in this study because the students did not stand to gain anything by responding in a particular way. Evaluations of Research Questions The SAMS was developed from multiple theo ristsÂ’ ideas regarding underachievement and how it can be impacted (e.g., Mandel & Marcus, 1995; Peters, 2000; Procha ska, et al., 1994; Rimm, 1995; Spevak & Karinch, 2000). Based on th ese conceptualizations the original SAMS would have had nine underlying components, or iginally promulgated as nine subscales. However, the factor analysis of student responses to the SAMS yielded five factors, which were subsequently converted to five subscales. Thus the nine constructs or iginally proposed were reorganized into five subscales based on the factor analysis. The translation of the nine originally pr oposed subscales into the five subscales was described in Chapter 4. In general, each of the nine constructs was presen ted in at least one of the five subscales. The Change Readiness cons truct was represented in three of the five subscales, organized according to the original categories of precontemplation, contemplation,
78 and action. The first subscale, De dication to Schoolwork, represente d the original constructs of Student Commitment and Self-Management Skills in addition to Change Readiness (action). The second subscale, Personal Well Being, was compri sed primarily of items from the constructs Mood Management and Personal Well Being. The third subscale was labeled Interpersonal Diplomacy and contained items from the origin al Interpersonal Diplomacy construct, the Independence/Dependence construct, and the Change Readiness (precontempl ation) construct. The fourth subscale was labeled Desire to Le arn and Succeed and was primarily comprised of the Student Achievement Expecta tions/Values construct items. Finally, the fifth subscale of Academic Self-Concept was comprised of items from the Self-Confidence/Self-Efficacy and Change Readiness (contemplation) constructs. The third research question a ddressed the reliability of the SAMS. The reliability coefficients for the current five subscales and the total score of the SAMS were all relatively high (see Table 4-5). These results indicate that the five-subscale fo rm of the SAMS is internally consistent and reliable. The fourth research question addressed possibl e age (represented by grade level) and/or gender differences in responses on the SAMS. Previous research regarding age differences in underachievement is ambiguous. Bruns (1992) found an increase in underachievement among Â“work-inhibitedÂ” underachieving students (i.e., those who underachieve because of a lack of effort) after elementary school. Preckel et al. (2006) found that 16% of the 7th-10th grade students in their study were underach ieving in school, but did not cl early state whether this rate of underachievement increased or decreased with age (or grade level). These types of studies give insight into the prevalen ce of academic underachievement, but the actual pervasiveness and difference in underachievement betw een age groups remain unclear.
79 The subscale scores for the SAMS were comp ared across four different age groups (i.e., grades six through nine). The analyses for subsca les one and five yielded statistically significant differences in responses across gr ade levels. For subscale one, Dedication to Schoolwork, grades 6 and 7 means were found to be significantly di fferent from the means for grades 8 and 9. Further, the means for the 6th and 7th graders were higher than those for the 8th and 9th graders. This finding suggests that dedi cation to schoolwork among under achievers decreases as they progress through school, which is consiste nt with the findings of Bruns (1992). Subscale five, Academic Self-Concept, also show ed a statistically significant main effect for grade level. The grade 6 means on this subs cale were found to be statistically significantly different from the grade 7 and grade 9 means. The means showed that the 6th graders scored significantly higher than students in grades 7 and 9 on this subscale. Again, this result suggests that underachieving students become less academ ically confident (i.e., have a lower academic self-concept) as they progress through school. Taken together, these results suggest that as students approach high school, their desire to work hard in school diminishes. There is ongoing debate about whether boys and girls achieve at different levels. Historically, data have supported the belief that boys underachieve more frequently than girls. However, theorists are still debating whether there is indeed a Â“gender gapÂ” in relation to actual achievement (Francis & Skelton, 2005). On subs cale four, Desire to Learn and Succeed, females scored significantly higher than males. This finding does not necessarily indicate that females are less likely to underachieve, but it does suggest that gender differences in underachievement still are worthy of investigation. However, overall, the results of these anal yses suggest a lack of gender-based differences in attitude s associated with underachievement.
80 The fifth research question of this study a ddressed the relationships among studentsÂ’ SAMS scores and their academic achievement. Th ere were statistically significant relationships between participantsÂ’ achievement in Mathematics and Reading and their SAMS subscale scores. Dedication to Schoolwork scores were positively and statistically signifi cantly correlated with Mathematics test scores, grades in Language Arts and Mathematics, and their cumulative grade point averages (GPA). Personal Well-Being was positively and statistically significantly correlated with studentsÂ’ grades in Language Arts and Mathematics and their GPAs. Interpersonal Diplomacy was positively and sta tistically significantly correlated with Mathematics and Reading test scores, Mathema tics and Language Arts grades, and GPAs. Desire to Learn and Succeed was positively and statistically significantly correlated with their Reading test scores, Language Arts and Mathem atics grades, and cumulative GPAs. Academic Self-Concept was positively and statistically significantly correlated with Reading and Mathematics test scores, La nguage Arts and Mathematics grades, and cumulative GPAs. Collectively, these results suggest that studentsÂ’ academic performance is correlated positively with their SAMS scores. Thus, the findings for research question five are consistent with the contentions of theorists who believe that student s who achieve will have higher desire to learn and set goals (McCoach & Siegle, 2003), lower levels of anxiety and depression (Mandel & Marcus, 1995), positive attit udes toward school (McCoach & Siegle, 2003), positive relationships with othe rs (Rimm, 1995), and higher academic self-concept (Lau & Chan, 2001). Implications The analyses of the SAMS data generated in this study yield implications for theorists of underachievement, school counselors who work w ith underachieving students, and researchers who study student underachievement.
81 Implications for Theory A plethora of theories on underachievement exist, likely because underachievement is a prevalent problem in schools today (West & Penne ll, 2003). Many of these theorists attempt to make their ideas on underachievement transition into professional education practice; however, so far this transition has been sluggish for several reasons. For example, Preckel, Holling, and Vock (2006) identified three obst acles to the research on underach ievement. First, the study of underachievement must be approached from mu ltiple perspectives because it is a complex concept. Second, the criteria for identifying under achievers have not been operationalized fully. Third, most of the research on underachieveme nt has been focused upon gifted students. Implications from the present study relate to each of these issues. Theorists and researchers have developed num erous typologies in the attempt to define more clearly the causes underlying student underachievement (e.g., Mandel & Marcus, 1995; Peters, 2000; Prochaska, et al., 1994; Rimm, 199 5; Spevak & Karinch, 2000). However, the many different perspectives of underachievement can lead to confusion. Rather than viewing these typologies as oppositional, this study pr esented a broad typology that took into account these different perspectives. The items for th e SAMS were developed based on four different typologies of underachievement, in addition to ideas from ProchaskaÂ’s theory of change. Therefore, it is possible to encompass the differing perspectives into a si ngular conceptualization instead of viewing them separately. Specifically the SAMS merged the ideas from each of the theories to develop one cohesive model that considers multiple perspectives of underachievement. The second problem Preckel et al. (2006) addre ssed was the lack of a substantive definition of an underachieving student. The identification of underachievi ng students was not addressed directly in this study, but it is one area theorists ne ed to continue to addres s. Once a substantive,
82 functional definition of an under achieving student is developed, the reasons underlying student underachievement can be more thoroughly invest igated and then presumably more clearly understood. In particular, the SAMS could be used as a research tool to help identify underachieving students. In addi tion to looking at a studentÂ’s test scores and grades, the studentÂ’s score on the SAMS could be used as an additional way to help identify whether the student is underachieving. The third problem Preckel et al. (200 6) addressed is the overemphasis among underachievement theories on gifted students. Wh ile the gifted population is certainly at-risk for underachievement, future research needs to fo cus on non-gifted students as well. The SAMS was developed from research on both gifted and nongifted students, and it is meant to be useful for any student population. Implications for Practice School counselors frequently work with students who are not achieving up to their potential, and parents and teachers frequently come to the school counselor searching for answers and ways to help the student stop the pattern of underachievement. A large amount of research is available on the topic of stude nt underachievement; however, most of the implications for practice are anecdotal and do not offer data-based suggestions for helping underachieving students. Therefor e, when school counselors enc ounter underachieving students, they either rely on anecdotal advice as presented in the literature and/or research or they rely upon (unstudied and/or unevaluated ) past experiences with under achieving students. Sometimes school counselors find the anecdotal advice or th eir past experiences allow them to help the underachieving student, but more often they do not. The SAMS has the pote ntial to assist counselors who ar e working with underachieving students. This assessment can be used to he lp to clarify the reas ons behind a studentÂ’s
83 underachievement. If the reasons for underach ievement are better understood, school counselors and researchers can test and evalua te intervention plans that dire ctly address those reasons. For example, if an underachieving student completes the SAMS and scores low on the Personal Well Being subscale, intervention plans that directly addre ss the studentsÂ’ depression, anxiety, and/or sense of belonging can be implemented. Further, if the student scores low on more than one subscale on the SAMS, the area needing the most a ttention could be addre ssed first and then the other areas would be addressed as time is available. Another important benefit the SAMS may provide for school counselors is that it may save them time when working with underachieving stud ents. If a school counselor simply asks an underachieving student to explain why s/he underach ieves, it is highly unl ikely that the student will be able to clearly and succi nctly pinpoint the reasons for hi s/her poor school performance. However, if an underachieving student completes the SAMS, the school counselor should have a clearer picture of reasons for th e studentÂ’s underachievement in less than half an hour. School counselors often have the patien ce to discuss underachievement w ith students, but it often takes several counseling sessions before the significa nt underlying reasons for underachievement can be uncovered. The SAMS thus has the potentia l to improve school counselorsÂ’ efficiency. The SAMS also has implic ations for educators besi des counselors, including administrators and teachers. E ducators need to be aware of th e different reasons for student underachievement. This background knowledge will enable teachers to more effectively meet studentsÂ’ needs. For example, if a teacher knows a student underachieves due to a lack of selfconfidence, the teacher can make more of an effort to complimen t and encourage the student and give him/her more opportunities to build ac ademic self-confidence in the classroom.
84 Additionally, administrators can help provide the school faculty with professional development opportunities to learn how to work with diffe rent types of underach ieving students. The SAMS has direct implicat ions for school counselors, te achers, and administrators. School counselors can actively e ducate the faculty in their school s about the different types of underachieving students. Intervention plans targeting a studentÂ’s specific reasons for underachievement can be implemented at home and at school to help the student end the pattern of underachievement. Recommendations There are several directions re searchers need to pursue in the study of underachievement, especially to continue to study underachieveme nt from a quantitative perspective. Much qualitative research has been conducted on under achievement, and many researchers have given anecdotal suggestions to help unde rachieving students. Qualitative research studies are valuable; however, more attention needs to be given to quantifying underachieve ment and the reasons underlying it. A first step researchers should take in this regard is to develop quantitative methods to identify underachieving students. Some research ers have begun to develop definitions of an underachieving student using such methods (e.g., Preckel et al., 2006 ). However, the definition of an underachieving student needs to be more cl early operationalized so that all researchers have one replicable method of identifying these students. The second step researchers need to take is to continue to investigate empirically the reasons underlying student underachievement. One way researchers can do this is by furthering the development of the SAMS. The five subscal es need to be supported through more research studies, with particular attenti on paid to the functioning of specific items. While the SAMS was reduced from 111 items to 62 items through this i nvestigation, its length may need to be scaled
85 down further. Future studies of the SAMS also should include participants from more regions of the U. S. as well as with more ethnically divers e populations. Similarly, it would be helpful to have student socioeconomic data so that th e relationship between subscale scores and socioeconomic background can be explored. And fi nally, it would be bene ficial to investigate how scores on the SAMS are associated with or va ry as a function of a variety of other student characteristics, including personality, other academic performance, and additional demographic characteristics. Once the definition of an underachieving student is more substantively operationalized, the SAMS is further established as a reliable and valid measure, a nd the relationships of the SAMS to diverse student characteristics are bette r understood, researchers can develop better explorations of intervention methods for undera chieving students. Researchers should then develop different intervention plans based on th e reasons for underachievement, including those uncovered by the SAMS. Subsequently, researchers should be able to test the effectiveness of each intervention plan and continue to revise and refine those plans. Thereafter, when a school counselor or other educator encounters an unde rachieving student, the methods for determining reasons for underachievement and the intervention pl ans will be clearly laid out. Such a process will, ultimately, save school counselors, students, parents, and teachers valu able time, and lead to increased student achievement. Summary The SAMS was developed with the underlyi ng goal of assisting educators and school counselors with identifying reason s behind student underachievement. Five factors that can help educators identify reasons behind student under achievement emerged from analysis of its properties: Dedication to School work, Personal Well Being, Interp ersonal Diplomacy, Desire to Learn and Succeed, and Academic Self-Concept. Th ese five subscales and the total score were
86 found to have high reliability. S ubsequently, a few variations in scores based on student gender or grade level were found. However, in genera l, there were not gendere d based differences in responding, and attitudes about sel ected aspects of underachievement decreased as school level increased. The continued development of a subs tantive definition of u nderachievement and the continued development of the SAMS should facilitate school counselorsÂ’ work with underachieving students.
87 APPENDIX A LETTER OF INVITATION Dear Practicing School Counselor, I am sending this email to middle and high school c ounselors because I am in need of your help! I am currently collecting data for my disse rtation study and I need your assistance with administering a survey to 7th-9th grade students. The purpose of the study is to further the development of a survey that will help counselor s identify and develop successful intervention plans for underachieving students. If you volunteer to help administer this surve y, you will be provided with all the necessary materials, including postage paid envelopes so ther e will be no mailing cost s. You will also be provided with step-by-step guidelines for admini stering the survey so the process will be straightforward. Each student who agrees to participate must also get his/her parent to sign an informed consent form. Once a studentÂ’s informed consent is re turned, you will give him/her a survey and a demographics sheet. After the student takes the survey, he/she will fold the survey into a prestamped envelope which you will mail separately. You will then fill out a brief school data sheet on each student. This school data sheet reque sts each studentÂ’s identification number, grade point average, and standardized test scores. You will then mail the student data sheet. The school identification numbers are necessary so the responses from the survey can be compared with the studentÂ’s grade point average and test scores. Assisting with the administration of the survey is completely voluntary. If you choose to provide your assistance, you may withdraw at any time. Student participants ma y also withdraw their consent at any time. All studentsÂ’ names and sc hool counselorsÂ’ names will be kept confidential to the extent provided by law. There are no anticipated risks to help administer the survey and there are no anticipated risks fo r the students taking the survey. It will take each student approximately 20-30 minutes to complete the survey. Thank you for taking the time to read this letter a nd for considering to offer your assistance. At the end of the research project, I would like to provide you with a summary of the results. If you wish to receive the results, please complete the request for study results and submit this separately from the survey. There are no other bene fits to you for volunteering to help with this study. However, at the end of this study, couns elors and researchers will have a better understanding of underachievement in 6th-9th grade students. If you have any questions regarding this letter, please email me at email@example.com Questions or concerns about the rights of participants can be sent to the UFIRB Office, Box 112250, University of Florida, Gaines ville, FL, 32611; phone (352) 392-0433. Thank you once again for your time. Carolyn A. Skinner Doctoral Candidate University of Florida
88 APPENDIX B IDENTIFYING PARTICIPANTS Each student taking the survey must fit all three of the following requirements: Each student must be in one of th e following age groups and grade levels: age 11 or 12 & in the 6th grade age 12 or 13 & in the 7th grade age 13 or 14 & in the 8th grade age 14 or 15 & in the 9th grade Student participant cannot have Specific Learning Disability (SLD) Each participant must be fluent in English
89 APPENDIX C INFORMED CONSENT LETTER Dear Parent/Guardian, My name is Carolyn Skinner and I am a gradua te student in the Depa rtment of Counselor Education at the University of Florida. I am conducting research on student achievement under the supervision of Dr. Larry Loesch. The purpose of this study is to further the development of a survey that measures studentÂ’s personality traits attitudes, and beliefs in regard to academic achievement. The survey is called the School Achievement Motivation Scales (SAMS). The results of this study may help school counselor s and teachers learn more effective ways of increasing student achievement. With your pe rmission, I would like to ask your child to volunteer for this research. A school counselor or teacher will administer the survey to partic ipating students. Students will take the survey on his/her school campus during school hours. The survey is not part of the regular class curriculum. If your student misses any regularly scheduled class work, he/she will be allowed to make it up. Participation in the surv ey will not affect your childÂ’s grade or status in the classroom. If all students in the class are pa rticipating in the survey, non-participants will be asked to sit quietly while the othe r students complete the survey. If you agree to allow your child to participate, he or she will be as ked to fill out a brief questionnaire which asks for basic background information (age, grad e level, gender, and ethnicity). Your child will then take the 115 item survey. Each student should take about 20-30 minutes to complete the survey. In addition to your studentÂ’s participation, I am asking the school counselor to provide me with your childÂ’ s grade point average a nd test scores. Your childÂ’s name will not be on any of the forms. Only his/her student identification number will be used. Your childÂ’s identity will be kept conf idential to the extent provided by law. You and your child have the right to withdraw consent for your ch ildÂ’s participation at any time without consequence. There are no known risks or immediate benefits to the participants. No compensation is offered for participation. Results of the study will be available in August, 2008 upon request. If you have any questions about this research project, please contact me by email at firstname.lastname@example.org or by phone at (561) 540-2416. You may also reach my supervisor, Dr. Larry Loesch at (352) 392-0371. Questions or concerns about th e rights of participants in this study can be sent to the UFIRB Office, Box 112250, University of Florida, Gainesville, FL, 32611-2250; phone (352) 392-0433. Thank you once again for your time. Carolyn A. Skinner Doctoral Candidate University of Florida
90 Please read and sign both sections below: Consent to take the SAMS I have read the procedure described above. I voluntarily give consent for my child, _________________________, to participate in Carolyn SkinnerÂ’s study of student achievement. I have received a copy of this description. _________________________ ________________ Parent/Guardian Date _________________________ ________________ 2nd Parent/Witness Date Consent for StudentÂ’s Info rmation to be Accessed I voluntarily give consent for academic information of my child, _________________________, to be provided to the researcher for the purpose of this study. I understand that this information includes grade point average and any available standardized test scores. _________________________ ________________ Parent/Guardian Date _________________________ ________________ 2nd Parent/Witness Date
91 APPENDIX D SCHOOL ACHIEVEMENT AND MOTIVATION SCALES Directions to Take the SAMS: The School Achievement Motivation Scales (SAMS) is designed to find out how you think and feel about yourself and your ab ilities, your learning and studyi ng, your efforts in school on a typical day, and your relations wi th others. The SAMS is made up of 111 statements describing you and your ideas. The statement may be not al l like you, very much like you, or somewhere in between. For each statement, choose the number in the following scale that best fits your response: 1= Not at all like me 2= Not very much like me 3= Somewhat like me 4= Much like me 5= Very much like me Try to answer according to how well the stat ement describes you. Ther e are no right or wrong answers. Please work as quickly as you can without being careless a nd please answer all the items. 1. I love learning new things. 2. I do not give up when I do poorly on an assignment or test. 3. I donÂ’t care if I finish high school as long as I can get a job. 4. I am lazy. 5. I learn quickly in school. 6. I get so nervous I can barely function. 7. I feel like I belong. 8. I have been getting help from people (e.g. tu toring, counseling, coaching) to improve my grades. 9. I like to get my way even if it makes others upset. 10. I keep track of when my sc hool assignments are due. 11. I am bored with school. 12. I do just enough work to get by in school.
92 13. I want to work on improving how I study for tests. 14. My success is up to me. 15. I am unsure about whether I should stay in school. 16. I get so nervous when I take a test that I donÂ’t do as well as I should. 17. I find life boring. 18. Adults think I have an Â“attitudeÂ” problem. 19. I am setting aside a certain amount of time for school work and sticking with it. 20. I often feel like I have no control over what happens to me in life. 21. I like school. 22. I feel hopeless about getting better grades. 23. I do not like being told what to do. 24. It is easy for me to stay focused when working on a school assignment. 25. I get my school work in on time. 26. I think I might be ready to work at trying to get better grades. 27. I think clearly. 28. I find I am depressed for no reason at all. 29. I trust others. 30. I tell people off if they get on my nerves. 31. I find it hard to stick to a study schedule. 32. I can calm myself down when I need to. 33. The most important part of school for me is being able to talk a nd socialize with my classmates. 34. When my schoolwork is difficult, I either give up or study only the easy parts.
93 35. I wish I had more ideas about how to be less tense when I take tests. 36. I focus on my strengths. 37. I have trouble falling asleep or staying asleep. 38. When I work hard in school, I do well. 39. I wish someone could help me figure out how to study for tests. 40. People talk about me behind my back. 41. I am really working hard at keeping my school assignments and paper organized. 42. It is important to me to get good grades in school. 43. I put off school assignments more than I should. 44. I do not feel good about who I am. 45. I want someone to help me figur e out how to study for tests. 46. I forget to do homework assignments. 47. I am able to influence others to my way of thinking. 48. I feel Â“blueÂ”. 49. I am critical of others 50. Even when school assignments are not interesting, I manage to work at them until I finish them. 51. All this talk about doing we ll in school is boring. 52. I worry that other people will be disappointed in me. 53. I waste time. 54. In my opinion, what is taught in my classes is not worth learning. 55. I know I need to talk with someone about how I can do better in school. 56. I do not have much to be proud of.
94 57. I plan for my future. 58. I can handle the stresses and pressures of school. 59. I worry about what I am going to do with the rest of my life. 60. My temper gets me in trouble. 61. I remember what IÂ’m supposed to do for homework. 62. I let others influence my decisions. 63. Being in school is a waste of time. 64. I am up to date in completing my school assignments. 65. I set high standards or goal s for myself in school. 66. I am a capable person. 67. I worry that I will get failing grades. 68. To me the future looks good. 69. I wish people would quit nagging me about my school work. 70. I like myself. 71. I argue with people I care about. 72. I spend so much time with my friends that my school work suffers. 73. It is just not that important to me to do well in school. 74. I finish what I start. 75. I think about what I am going to do with the rest of my life. 76. I hide my feelings. 77. I donÂ’t want to waste my time thinking about school. 78. I am not very smart. 79. I get depressed easily.
95 80. I have friends I can rely upon. 81. I need help figuring out how to do my school assignments. 82. I am spending more time working on my school assignments. 83. I feel like I am just Â“going through the motions.Â” 84. I find it easy to relax. 85. I am well organized. 86. Doing well in school is important for my future career goals. 87. I work well with others. 88. I give up easily. 89. Talking about getting good grades is boring. 90. I feel that I am a successful person. 91. I get very tense when I study. 92. I am Â“right on courseÂ” in figuring out what I want to do with my life. 93. I am a happy person. 94. I set aside a certain amount of time to do schoolwork and I stick with it. 95. I get blamed for things I didnÂ’t do. 96. I would rather coast thro ugh school then spend a lot of time doing schoolwork. 97. I have trouble deciding what I want to do in life. 98. I am actually doing something to improve how I study for tests. 99. I come to class unprepared. 100. ItÂ’s a waste of my time to plan for my future. 101. I have interests outside of school that are more important to me than getting good grades. 102. I work hard to get a good grade even when I donÂ’t like a class.
96 103. As far as I am concerned, how I do in school is no oneÂ’s business but my own. 104. I sleep well. 105. I blame myself for things. 106. I only study when there is the pressure of a test 107. I get along well with most of my teachers. 108. I say what I feel. 109. I am easily discouraged. 110. I am really working hard at keeping up to date on my school assignments. 111. I check my assignments before I turn them in.
97 APPENDIX E DIRECTIONS FOR TA KING THE SURVEY Counselors/Teachers: These directions are on th e informed consent page of the computerized survey. I have printed them out for y ou in case students have any questions. Directions to Take the Survey: The first four questions on this survey ask you information about yourself. Please answer these four questions to the best of your ability. The School Achievement Motivation Scale (SAMS) is designed to find out how you think and feel about yourself and your ab ilities, your learning and studyi ng, your efforts in school on a typical day, and your relations wi th others. The SAMS is made up of 111 statements describing you and your ideas. The statement may be not al l like you, very much like you, or somewhere in between. For each statement, choose the number in the following scale that best fits your response: 1= Not at all like me 2= Not very much like me 3= Somewhat like me 4= Much like me 5= Very much like me Try to answer according to how well the stat ement describes you. Ther e are no right or wrong answers. Please work as quickly as you can without being careless a nd please answer all the items.
98 APPENDIX F SURVEY ADMINISTRATOR C ONFIDENTIALITY AGREEMENT Dear Survey Administrator, Thank you for taking the time to assist with this research study. Please sign the confidentiality agreement below and return in the postage paid envelope. Sincerely, Carolyn Skinner Doctoral Candidate University of Florida I, ______________________________, agree to keep all studen t responses and student data sheets completely confidential. No student names will be used on any of the forms, only student identification numbers. I agree to keep all of the forms in a safe locked place or under my supervision at all times. _________________________________ _________________ Signature Date
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BIOGRAPHICAL SKETCH Carolyn Skinner was born in 1978, in Oklahoma, and was raised from the age of 10 in St. Louis Park, Minnesota. She is th e only daughter of parents John and Deborah Skinner. Carolyn received her Bachelor of Arts degree in psychol ogy from Northwestern University in 2000. In 2003, she received her Master of Education and Specialist in E ducation degrees in counseling and school guidance from the University of Florida. Carolyn then finished her doctoral coursework in Gainesville, where she also served as a school counselor at P.K. Yonge Developmental Research School. In 2005, Caro lyn moved to Palm Beach County where she currently works as a school counselor and guida nce coordinator of a high school in West Palm Beach.