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Student characteristics and self-concept of secondary career and technical education students in a north central Texas region

Dissertation
Author: Nancy Lynne Cox
Abstract:
Self-concept, discussed as a scholarly topic since the time of Socrates and Plato, is an important theoretical construct in education because self-concept is considered to be a desirable trait and a facilitator of positive future behavior. The purpose of this study was to examine the relationship between the characteristics of students enrolled in career and technical education (CTE) programs and students' self-concept scores as measured by specific subscales from the Self-Description Questionnaire (SDQ). A total of 196 male and 89 female secondary students (Grades 9-12) enrolled in arts, audio/video technology and communications cluster courses in North Central Texas school districts participated in the study. Student characteristic variables of interest were age, gender, CTE program enrollment, and participation in CTE. The self-concept subscales analyzed were General, Academic, Verbal, Math, and Problem Solving. A canonical correlation analysis was conducted using the four student characteristic variables as predictors of the five self-concept variables to evaluate the multivariate shared relationship between the two variable sets. The full model across all functions explained about 23% of the variance between the variable sets. Function 1 explained 15% of the shared variance and Function 2 explained 7% of the variance that remained. This study detected a relationship between specific student characteristics and self-concept as measured on certain domain-specific first-order factors. Gender and participation in CTE were found to be related to verbal self-concept and problem-solving self-concept. Results suggest that females in arts-based CTE programs have a higher verbal self-concept than their male counterparts; male students have a higher problem-solving self-concept. Results further suggest that students with a high level of participation in CTE also have high verbal and problem-solving self-concepts.

iv TABLE OF CONTENTS Page ACKNOWLEDGEMENTS ............................................................................................ iii LIST OF TABLES ......................................................................................................... vi LIST OF FIGURES ....................................................................................................... vii CHAPTER 1. INTRODUCTION ............................................................................................... 1 Background and Significance of the Study Need for the Study Theoretical Framework Purpose of the Study Research Question Limitations Delimitations Definition of Terms Summary 2. LITERATURE REVIEW ..................................................................................... 13 Career and Technical Education Super’s Occupational Development Self-Concept Theory Self-Concept Summary 3. METHODOLOGY .............................................................................................. 29 Introduction Research Design Instrument Population Data Collection Procedures

v Data Scoring Procedures Data Analysis Procedures Summary 4. RESULTS .......................................................................................................... 54 Introduction Data Assessment Statistical Assumptions Data Analyses Summary 5. DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS ........................ 80 Introduction Discussion of Findings Conclusions Recommendations Summary APPENDICES .............................................................................................................. 88 REFERENCES .......................................................................................................... 121

vi LIST OF TABLES Page 1. Demographic Composition of Student Population in Major Urban Regions in Texas ............................................................................................................... 37 2. Negatively-Worded Survey Statements ............................................................... 55 3. SDQ Subscale Items ........................................................................................... 57 4. Demographic Composition of Student Population in Study, Region, and State .. 59 5. Courses Listed on Survey and Reason for Elimination From Dataset ................. 61 6. CTE Courses Taken, Credit Range, and Weight Used to Calculate Student Level of Participation in CTE ............................................................................... 63 7. Distributional Descriptives for Study Data ........................................................... 66 8. Canonical Correlation Dimension Reduction Analysis ........................................ 69 9. Canonical Analyses for Function 1 ...................................................................... 71 10. Canonical Analyses for Function 2 ...................................................................... 72 11. Commonality Data: Partitioned Variance of Function 1's Student Characteristics (Predictor) Canonical Variate ...................................................... 74 12. Commonality Data: Partitioned Variance of Function 1's Self-Concept (Criterion) Canonical Variate ............................................................................... 75 13. Commonality Data: Partitioned Variance of Function 2's Student Characteristics (Predictor) Canonical Variate ...................................................... 76 14. Commonality Data: Partitioned Variance of Function 2's Self-Concept (Criterion) Canonical Variate ............................................................................... 77 15. Complete Sample Correlation Matrix .................................................................. 78

vii LIST OF FIGURES Page 1. Diagram of the canonical correlation analysis ....................................................... 47 2. Chi-square by Mahalanobis distance for 285 cases on all research variables ...... 68

1 CHAPTER 1 INTRODUCTION Background and Significance of the Study Self-concept as a theoretical construct is important to the field of education because a positive self-concept is considered to be a desirable trait as well as a facilitator of positive future behavior (Marsh, 1993). Positive student self-concept has been linked to academic achievement in core classes (Marsh, Smith, & Barnes, 1985), outcomes of specific performance arts programs (Marsh & Roche, 1996), and positive classroom characteristics in the domains of cooperation, persistence, leadership, anxiety, expectations for future schooling, family support, behavior in class, and peer interactions (Hay, Ashman, & Van Kraayenoord, 1998). Self-concept has been discussed as a scholarly topic since the time of Socrates and Plato (J. Hattie as cited in Vispoel, 2000). Initial research in the 1960s, published by Coopersmith and Piers, defined self-concept as a global, unidimensional construct, which resulted in conflicting findings and strong criticism from other researchers (Vispoel, 2000). Research by Shavelson, Hubner, and Stanton (1976) led to the development of a multidimensional, hierarchical model, referred to as the Shavelson model (Leach, Henson, Odom, & Cagle, 2006). Substantial progress has been made in self-concept research methodology, theory, and instrument development in subsequent years (Vispoel, 2000). Research by Marsh and Shavelson (1985) and Byrne and Shavelson (1986) confirmed the multidimensional, hierarchical nature of self-concept (Leach et al., 2006). Due to this multidimensionality, self-concept may vary according to domain; the way we think about and categorize ourselves as a “math” or “English”

2 person, as “creative” or “athletic,” or as “beautiful” or “intelligent” is a practical example of the domain-specific nature of self-concept (Marsh, Craven, & McInerney, 2008). High or low self-concept in one domain does not necessarily correlate with high or low self- concept in another domain. General self-concept, also called self-esteem, is an overall view of oneself that is not generally correlated with domain-specific self-concept. General self-concept, typically found to be stable over time (Marsh, 2005), is considered by laypersons and professionals to be an important component in understanding human behavior (Wylie, 1989) and is considered by many researchers to be the basis for all motivated behavior (Franken, 1994). General self-concept is based on personal thoughts, interpretations, and beliefs: “It is not how good (or bad) you really are, but how good (or bad) you think you are that determines your behavior” (Bandura, 2003, p.377). According to Bandura (2003), individuals with high general self-concept set more challenging goals for themselves and are more persistent in the face of adversity than their counterparts with low general self-concept. Need for the Study The study of self-concept has a long history of appealing to researchers from many disciplines (Marsh, Relich, & Smith, 1983). According to Bracken and Mills (1994), “Over 11,000 research studies cited in the American Psychological Association’s PyscINFO 1974-1992 database are related to self-concept or self-esteem and thousands more are cited in the ERIC database” (p.1). Identified through a search of the ERIC and PsycINFO databases using self-description questionnaire, self description questionnaire, and SDQ as the search terms, more than 100 peer-reviewed journal

3 articles were published prior to 2004 documenting self-concept research conducted utilizing Marsh’s Self-Description Questionnaire (SDQ; Leach et al., 2006). From January 2004 to December 2008, an additional 35 peer-reviewed articles have been published documenting research conducted with one of the Marsh SDQ instruments. Topics of interest in these 35 recent peer-reviewed articles include self-concept in deaf students, high-ability college students, gifted secondary students, students with mild intellectual disabilities, children with cerebral palsy, and students from various cultures. One article identified in this search draws conclusions relative to the science, technology, engineering, and mathematics fields, which are part of the career and technical education (CTE) curriculum. Another search of the primary CTE journals (identified by the University Council for Human Resource Education), using self- concept, self concept, and vocational as search terms, yielded only one article (Greenan & Wu, 1994) that addressed the topic of self-concept of students in vocational programs. Considering the value of self-concept as a theoretical construct, there is an obvious lack of documented research in the area of self-concept as it relates to students participating in CTE programs. In Texas public high schools (Grades 9-12), students spend approximately 8 hours a day in a classroom environment. Texas students may spend up to 2 hours each day, roughly one fourth of the school day, in one CTE class. In some districts students have the same CTE teacher all 4 years of high school as they work to complete a coherent sequence of courses. It seems logical, therefore, to investigate the particular relationship between participation in CTE and student self-concept.

4 Theoretical Framework This section outlines the theoretical framework for the study. A brief overview is provided for Super’s occupational development self-concept theory and for the Marsh/Shavelson model of self-concept. Super’s Occupational Development Self-Concept Theory Donald Super believed that “the process of vocational development is essentially that of developing and implementing a self concept” (Super, 1953, p. 189). Super (1963a) referred to the 1950s work of Sarbin in his utilization of the term self-concept as an “individual’s picture of himself, the perceived self with accrued meanings . . . a picture of the self in some role, some situation, in a position, performing some set of functions, or in some web of relationships” (p. 18). One component of Super’s (1953) theory is the primary focus of this project: Vocational preferences and competencies, the situations in which people live and work, and hence their self concepts, change with time and experience (although self concepts are generally fairly stable from late adolescence until late maturity), making choice and adjustment a continuous process (p. 189). The dynamic nature of Super’s occupational choice and self-concept development theory may serve to increase an understanding of the development of self- concept related to occupational choice. There has been some expressed concern due to a lack of substantive research supporting Super’s theory (Salomone, 1996). Investigating the entire developmental scaffold of the theory is beyond the scope of this research. This study focuses on the adolescent stage of development, investigating in

5 particular the relationship between characteristics of CTE students and various facets of their self-concepts. Marsh/Shavelson Model of Self-Concept The current, generally accepted self-concept model, referred to as the Marsh/Shavelson model of self-concept, is rooted in the work of Shavelson et al. (1976). Shavelson et al. defined self-concept as an individual’s self-perceptions formed through experience with and interpretation of one’s environment as influenced by the assessments of significant others, reinforcement, and personal ascriptions for one’s own behavior (Marsh, 2005). The Shavelson et al. model includes an overall measure of self-concept (general self-concept), two higher order factors (academic self-concept and non-academic self-concept), and a number of domain-specific self-concept subscales. In the early 1990s, as a result of experiencing difficulties with the existing self- concept measurement instruments in differentiating among the broad self-concept domains, Marsh developed the Self-Description Questionnaire (SDQ) instruments to support self-concept research (Marsh, 2005). Research based on the SDQ family of instruments (Marsh, n. d., 1989; Marsh & Shavelson, 1985; Marsh, Byrne, & Shavelson, 1988) led to the Marsh/Shavelson revision of the Shavelson et al. (1976) model. This Marsh/Shavelson revision called for the separation of the academic higher order factor into two higher order academic factors – math/academic and verbal/academic. Additional research by Marsh et al. (1988) has led to support for another revision of the model, creating an even more complex self-concept structure that includes a wider variety of specific academic self-concept domains. In addition to measuring the generally agreed upon subscales (physical appearance, peer relations, parent relations,

6 and honesty self-concepts), the revised Marsh/Shavelson model also measures self- concept related to physical abilities, emotional stability, spiritual values/religion, problem solving, and a wide range of academic areas (Bracken & Mills, 1994; Marsh, 2005). Purpose of the Study The purpose of this study was to examine the relationship between the characteristics of students enrolled in arts, audio/video technology and communications (AAVTC) cluster CTE programs and students’ self-concept scores as measured by specific subscales from the Self-Description Questionnaire (Marsh, n.d., 1989). Using a 6-point Likert scale with values ranging from false (not like me at all) to true (very much like me), students responded to a variety of questions relating to how they think and feel about themselves in terms of school-related subjects. Research Question In selected secondary CTE AAVTC cluster programs in Texas, the study sought to answer the following research question: What is the relationship between CTE student characteristics and self-concept? Limitations 1. This study considered only responses from students currently enrolled in five of the public secondary (Grades 9-12) courses in the AAVTC career cluster. 2. This study did not consider the self-concept of teachers assigned to teach in the classrooms identified for participation in the study. 3. This study was limited because of the lack of attention to the nestedness of the data in selecting a research methodology. Canonical correlation analysis (CCA)

7 methods, while honoring the complexities of the constructs, did not meet the assumption of independence of observations. Delimitations 1. This research examined students’ self-reported self-concept scores while in high school as measured by subscales of the SDQII and the SDQIII. 2. This study examined students’ perceived self-concept. The study did not incorporate perceptions or reports from teachers, counselors, administrators, parents, peers, or others regarding individual students’ self-concept. 3. This study focused on high school students enrolled in public CTE AAVTC cluster programs of study in a North Central Texas region in the United States. Based on the available student enrollment data, programs investigated in this study included (a) advertising design/visual arts and design; (b) animation; (c) commercial photography, (d) graphic arts/printing and imaging technology; and (e) media technology. 4. This study assumed that students enrolled in the CTE programs involved in the study participated in the CTE programs by their own choice. 5. Data collected using the SDQ II instrument were made available in electronic form to the SELF Research Centre as part of the Conditions of Use. Definition of Terms  Arts, audio/video technology and communications cluster (AAVTC): The AAVTC cluster focuses on designing, producing, exhibiting, performing, writing, and publishing multimedia content including visual and performing arts and design,

8 journalism, and entertainment services (States’ Career Clusters Initiative [SCCI], 2008).  Career and technical education (CTE): These are organized educational activities that— (A) offer a sequence of courses that— (i) provides individuals with coherent and rigorous content aligned with challenging academic standards and relevant technical knowledge and skills needed to prepare for further education and careers in current or emerging professions; (ii) provides technical skill proficiency, an industry-recognized credential, a certificate, or an associate degree; and (iii) may include prerequisite courses (other than a remedial course) that meet the requirements of this subparagraph; and (B) include competency-based applied learning that contributes to the academic knowledge, higher-order reasoning and problem-solving skills, work attitudes, general employability skills, technical skills, and occupation-specific skills, and knowledge of all aspects of an industry, including entrepreneurship, of an individual. (Carl D. Perkins Career and Technical Education Improvement Act of 2006 [Perkins IV], 2006, p. 3)  Coherent sequence of courses: A coherent sequence of courses is defined by the Texas Education Agency as two or more CTE courses for three or more credits (Texas Education Agency [TEA], 2007b).

9  Community types: Districts are classified on a scale ranging from urban to rural. Community types are as follows: Major urban – The largest school districts in the state that serve the six metropolitan areas of Houston, Dallas, San Antonio, Fort Worth, Austin, and El Paso. Major urban districts are the districts with the greatest membership in counties with populations of 725,000 or more, and more than 35% of the students are identified as economically disadvantaged. In some cases, other size threshold criteria may apply. Major suburban – Other school districts in and around the major urban areas. Generally speaking, major suburban districts are contiguous to major urban districts. If the suburban district is not contiguous, it must have a student population that is at least 15% of the size of the district designated as major urban. In some cases, other size threshold criteria may apply. Other central city – The major school districts in other large, but not major, Texas cities. Other central city districts are the largest districts in counties with populations between 100,000 and 724,999 and are not contiguous to any major urban districts. In some cases, other size threshold criteria may apply. Other central city suburban – Other school districts in and around the other large, but not major, Texas cities. Generally speaking, other central city suburban districts are contiguous to other central city districts. If the suburban district is not contiguous, it must have a student population that is at least 15% of the largest district enrollment in the county. Its enrollment is greater than 3% of

10 the contiguous other central city district. In some cases, other size threshold criteria may apply. Independent town – The largest school districts in counties with populations of 25,000 to 100,000. In some cases, other size threshold criteria may apply. Non-metro: Fast growing – School districts that are not in any of the above categories and that exhibit a five-year growth rate of at least 20%. These districts must have at least 300 students in membership. Non-metro: Stable – School districts that are not in any of the above categories, yet have a number of students in membership that exceeds the state median. Rural – School districts that do not meet the criteria for placement into any of the above categories. These districts either have a growth rate less than 20% and the number of students in membership is between 300 and the state median, or the number of students in membership is less than 300. (TEA, 2009c)  Economically disadvantaged students are those who are reported as eligible for free or reduced-price meals under the National School Lunch Program and Child Nutrition Program or other public assistance. Students reported with any one of these status codes may or may not be enrolled in a special program such as compensatory or special education (TEA, 2008).  Educational Service Center (ESC): Established by the Texas State Legislature and State Board of Education in 1967,

ESCs provide state leadership for special

11 education-related functions and services for school districts within defined geographical areas. There are 20 ESC regions in Texas (TEA, 2009d).  Perkins IV: Perkins IV refers to the Carl D. Perkins Career and Technical Education Improvement Act of 2006, signed into law by President George W. Bush on August 12, 2006.  Public Education Information Management System (PEIMS): The PEIMS encompasses all data requested and received by TEA about public education, including student demographic and academic performance, personnel, financial, and organizational information. Special education data are reported by local education agencies (school districts and charter schools) to the TEA throughout the school year (TEA, 2007).  Self-concept: a person’s self-perceptions formed through experience with and interpretation of one’s environment as influenced by the assessments of significant others, reinforcement, and personal ascriptions for one’s own behavior (Marsh, 2005).  State Board of Education (SBOE): The Texas State Board of Education establishes policy and provides leadership for the Texas public school system. The board works with the commissioner of education and the Texas Education Agency to facilitate the operation of Texas’ public school system consisting of 1,227 school districts and charter schools, approximately 7,900 campuses, more than 590,000 employees, and more than 4.5 million students (TEA, 2009e).  Texas Education Agency (TEA): The Texas Education Agency is the administrative unit for primary and secondary public education. The mission of

12 the Texas Education Agency is to provide leadership, guidance, and resources to help schools meet the educational needs of all students (TEA, 2008). Summary This chapter provides background on self-concept as a theoretical construct and identifies a need to examine student self-concept with regard to CTE student characteristics. The chapter also outlines a theoretical framework and purpose for the proposed study. Lastly, the chapter defines the research questions, hypotheses, and assumptions that serve as the foundation of the study. Chapter 2 reviews existing literature related to the study.

13 CHAPTER 2 LITERATURE REVIEW Chapter 2 reviews the literature relevant to the present study. This chapter is structured into three topics of interest. The first topic focuses on career and technical education (CTE). The second topic addresses Super’s occupational development self- concept theory and current research testing various components of the theory. The third topic examines the Marsh/Shavelson model of self-concept and current self- concept research conducted with the Self-Description Questionnaire (SDQ). Career and Technical Education Prior to the passage of the Carl D. Perkins Career and Technical Education Improvement Act of 2006 (Perkins IV), the most current piece of federal CTE legislation, CTE had been referred to in legislation using the terms vocational education, applied technology, and work. The term occupational education has also been applied to describe the educational activities currently associated with CTE. “The history of work education (vocational education) is very, very old, perhaps beginning with the use of stone tools in the Paleolithic period (old stone age) about 2,500,000 years ago” (Scott and Sarkees-Wircenski, 1996, p.49). CTE has evolved over time from instruction regarding the use of stone tools to include such areas as audio and video technology, architectural and interior design, forensic science, and engineering and robotics. CTE programs have been federally funded since the passage of the Smith- Hughes Act of 1917. Significant pieces of legislation have been enacted since the Smith-Hughes Act: the Vocational Education Act of 1963 (amended in 1968 and 1976); the Carl D. Perkins Vocational Education Act of 1984; the Carl D. Perkins Vocational

14 and Applied Technology Act of 1990 (Perkins II); the National School-to-Work Opportunities Act of 1994; the Goals 2000: Educate America Act of 1994; and the Carl D. Perkins Act of 1998 (Perkins III). Scott and Sarkees-Wircenski (1996) provided a thorough discussion of the evolution of CTE, and Threeton (2007) provided a brief sketch of legislative history related to CTE. A review of the history of CTE shows that federal legislation has largely impacted the development and focus of CTE programs since 1917 (Threeton, 2007). Perkins IV defines CTE as organized education that provides students with a coherent sequence of courses focusing on competency-based applied learning. CTE curriculum, by definition, must include “academic knowledge, higher-order reasoning and problem-solving skills, work attitudes, general employability skills, technical skills, and occupation-specific skills, and knowledge of all aspects of an industry, including entrepreneurship, of an individual” (Perkins IV, p.4) Many CTE teachers would likely agree that these requirements, although new to the federal definition of CTE, have been part of the curriculum in CTE programs for years. Career Clusters What began in 1996 as a joint effort between the National Skills Standards Board (NSSB), the National School-to-Work Office (NSTWO), and the Office of Vocational and Adult Education (OVAE) to create curricular frameworks in broad career areas related to manufacturing and health services eventually became a project supported entirely by the Department of Education (DOE) in 1997. Over the course of 2 years and a number of successful states’ grants, the DOE was able to develop standards and pathways for three career clusters: information technology, transportation/distribution and logistics,

15 and arts/audio video technology. In 1999 OVAE identified 16 broad categories of occupations, commonly referred to as the 16 career clusters (States’ Career Clusters Initiative [SCCI], 2008): 1. Agriculture and natural resources 2. Architecture and construction 3. Arts, audio/video technology and communications 4. Business management and administration 5. Education and training 6. Finance 7. Government and public administration 8. Health services 9. Hospitality and tourism 10. Human services 11. Information technology 12. Law, public safety, corrections and security 13. Manufacturing 14. Marketing 15. Science, technology, engineering and mathematics 16. Transportation, distribution and logistics According to Ruffing (2006), in an interview with U.S. Secretary of Education Richard Riley, Secretary Riley stated that the clusters were seen as “a whole new approach” to CTE (p. 5). Clusters became a method of organizing new CTE curricula which would focus on “higher order workplace skills; integrated career development;

16 occupational training that emphasized both breadth and depth; and integrated academics” (Ruffing, 2006, p. 5). Under the new framework, each cluster has three levels of knowledge and skills standards: foundational, pathway, and specialty. According to Ruffing, the cluster framework represented a change in CTE that was seen by CTE state directors as detrimental to the quality of programs currently offered. In response to this change, the CTE state directors drafted a vision paper to describe the future role of CTE. As the vision developed over the course of a year, the state directors began to see an opportunity to use the States Career Clusters Initiative (SCCI) as a vehicle to achieve their vision for CTE. About this same time, OVAE began requiring states to use career clusters as a method for reporting student enrollment to meet Perkins accountability requirements. In 2000 the National Association of State Directors of Career and Technical Education consortium (NASDCTEc) applied for and received (in 2001) a grant to develop the remaining 11 clusters. The Oklahoma Department of Career and Technology Education (ODCTE) served as the clearinghouse and fiscal agent for this grant project. Validated by more than 1,000 people in all 50 states, the resources for all 16 career clusters were unveiled by NASDCTEc in September 2002. Around the time of the unveiling, OVAE notified Oklahoma that it would not renew funding under the original cooperative agreement. Consequently, NASDCTEc took ownership of both managing and funding the SCCI using reserve funds, voluntary state assessments, the annual Career Cluster Institute revenue, and the sale of products. Around 2005 it was reported to NASDCTEc that, with the funding of a grant titled Career Pathways – A Framework for Career Planning and Preparation in the 21 st

17 Century, Texas would begin investigating a plan to transition from the traditional six CTE service programs to full implementation of the career clusters framework. As part of that grant project, it was decided that Texas would adopt all 16 career clusters and utilize the SCCI resources as the framework for identifying and developing career pathways specific to Texas. The initiative that grew out of that grant came to be known as AchieveTexas. The AchieveTexas framework was rolled out to educational stakeholders in July 2006 to coincide with statewide professional development conferences. The initial roll-out included products related to (a) implementation of the entire framework for districts, administrators, and teachers and (b) identification of recommended pathways for students, parents, teachers, and guidance counselors (TEA, 2006). Subsequent products developed under the AchieveTexas initiative have included a cluster guide for each of the 16 career clusters, posters to promote AchieveTexas, and a resource guide for counselors in English and in Spanish. In 2007 Texas began revisions of the Texas Essential Knowledge and Skills (TEKS) standards for CTE. In May 2007, the 80th Texas Legislature passed HB 3485, which required the State Board of Education (SBOE) to revise the CTE TEKS by September 1, 2009. In fall 2007, the SBOE appointed individuals from across the state to writing teams who were charged with the task of making recommendations for revisions to the CTE TEKS. Writing teams began meeting in spring 2008, to review the current CTE TEKS and make recommendations for revisions (TEA, 2009e). Much of the work related to CTE TEKS revision focused on aligning programs, courses, and standards with the framework of the 16 career clusters.

18 Arts, Audio/Video Technology and Communications Cluster According to the SCCI, the arts, audio/video technology and communications cluster (AAVTC) includes the design, production, exhibition, performance, writing, and publishing of multimedia content (SCCI, 2008). The cluster, as federally defined, includes the following six pathways: (a) audio and video technology and film, (b) printing technology, (c) visual arts, (d) performing arts, (e) journalism and broadcasting, and (f) telecommunications. Each of the pathways identifies sample careers students might consider at various levels of education and training. The pathways identified in Texas are a little narrower, based on the current structure of the curriculum division at the Texas Education Agency, which separates fine arts and CTE. Consequently, in Texas the AAVTC cluster does not address the performing arts or telecommunications pathways, nor does it address the full scope of the sample careers outlined in the visual arts pathway. As mentioned in the preceding section, much of the focus of the CTE TEKS writing teams was to align programs and courses to the framework of the 16 career clusters. As a result of the CTE TEKS revision process, the new AAVTC TEKS include the following program areas: (a) animation, (b) audio/video technology, (c) commercial photography, (d) graphic design and illustration, (e) fashion, and (f) printing and imaging technology, which can be considered within the pathways framework. Printing and imaging technology directly corresponds to the printing technology pathway. Audio/video technology relates to the audio and video technology and the journalism and broadcasting pathways. Animation, commercial photography, graphic design and illustration, and fashion are all distinct components of the visual arts pathway. The arts,

Full document contains 139 pages
Abstract: Self-concept, discussed as a scholarly topic since the time of Socrates and Plato, is an important theoretical construct in education because self-concept is considered to be a desirable trait and a facilitator of positive future behavior. The purpose of this study was to examine the relationship between the characteristics of students enrolled in career and technical education (CTE) programs and students' self-concept scores as measured by specific subscales from the Self-Description Questionnaire (SDQ). A total of 196 male and 89 female secondary students (Grades 9-12) enrolled in arts, audio/video technology and communications cluster courses in North Central Texas school districts participated in the study. Student characteristic variables of interest were age, gender, CTE program enrollment, and participation in CTE. The self-concept subscales analyzed were General, Academic, Verbal, Math, and Problem Solving. A canonical correlation analysis was conducted using the four student characteristic variables as predictors of the five self-concept variables to evaluate the multivariate shared relationship between the two variable sets. The full model across all functions explained about 23% of the variance between the variable sets. Function 1 explained 15% of the shared variance and Function 2 explained 7% of the variance that remained. This study detected a relationship between specific student characteristics and self-concept as measured on certain domain-specific first-order factors. Gender and participation in CTE were found to be related to verbal self-concept and problem-solving self-concept. Results suggest that females in arts-based CTE programs have a higher verbal self-concept than their male counterparts; male students have a higher problem-solving self-concept. Results further suggest that students with a high level of participation in CTE also have high verbal and problem-solving self-concepts.