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University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations Dissertations and Theses July 2018 STEM PIPELINE FOR STUDENTS WITH DISABILITIES: FROM HIGH SCHOOL TO INTENTIONS TO MAJOR IN STEM Joshua Bittinger University of Massachusetts Amherst Follow this and additional works at: https://scholarworks.edu/dissertations_2 Part of the Disability and Equity in Education Commons, Higher Education Commons, and the Science and Mathematics Education Commons Recommended Citation Bittinger, Joshua, "STEM PIPELINE FOR STUDENTS WITH DISABILITIES: FROM HIGH SCHOOL TO INTENTIONS TO MAJOR IN STEM" (2018).edu/dissertations_2/1313 This Open Access Dissertation is brought to you for free and open access by the Dissertations and Theses at ScholarWorks@UMass Amherst. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact scholarworks@library. STEM PIPELINE FOR STUDENTS WITH DISABILITIES: FROM HIGH SCHOOL TO INTENTIONS TO MAJOR IN STEM A Dissertation Presented by JOSHUA D.

BITTINGER Submitted to the Graduate School of the University of Massachusetts Amherst in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY May 2018 College of Education Higher Education © Copyright by Joshua D. Bittinger 2018 All Rights Reserved STEM PIPELINE FOR STUDENTS WITH DISABILITIES: FROM HIGH SCHOOL TO INTENTIONS TO MAJOR IN STEM A Dissertation Presented By JOSHUA D. BITTINGER Approved as to style and content by: _________________________________________ Ryan S. Wells, Chair _________________________________________ Ezekiel W.

Kimball, Member _________________________________________ Joya Misra, Member __________________________________________ Jennifer Randall Associate Dean of Academic Affairs College of Education DEDICATION To my mom, for always being supportive of my pursuit of education, even if at times it did not make sense. To Rachel, who helped me through the ups and downs of this journey and has not held that against me. To all of the students out there who experience disability as they move through their educational journey, both diagnosed and undiagnosed. ACKNOWLEDGMENTS I would be remiss if I did not thank my committee (Drs.

Ryan Wells, Ezekiel Kimball, and Joya Misra) for their gracious support and feedback during my dissertation journey. This document shifted multiple times through our conversations, and I know that those adjustments added considerable strength to this work. Ryan has helped steer me through my doctoral education, starting from my initial application to the program. v ABSTRACT STEM PIPELINE FOR STUDENTS WITH DISABILITIES: FROM HIGH SCHOOL TO INTENTIONS TO MAJOR IN STEM MAY 2018 JOSHUA D., UNIVERSITY OF MARYLAND, COLLEGE PARK Ph., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ryan S.

Wells This dissertation examined the science, technology, engineering, and math (STEM) major declaration intentions of students with disabilities as they graduated high school and entered college. I used data from the High School Longitudinal Study of 2009 (HSLS:09) because data collection began in high school and followed students into college, facilitating research focusing on access. Before investigating major declaration intentions, I critiqued the definition and measurement of disability in the HSLS:09, drawing from survey research methods literature. The two subsequent analyses focused on psychological and structural components, respectively.

My focus on psychological components drew from Eccles and colleagues’ (1983) expectancy-value framework. This framework tapped into the valuation that students placed on math- and science-related concepts and their expectations to succeed in those fields. Structural components explored in the final analysis drew from human, cultural, and social capital theories. These three theories were at the core of Perna’s (2006) model of college choice, which I vi adapted to predict majoring in STEM.

Both analyses utilized multiple logistic regression to create prediction models. Findings suggested that college-bound students with ADHD have higher odds of intending to pursue STEM majors, compared to students experiencing other forms of disability. Psychological and structural measures were also positively related with odds of pursuing these majors. Implications highlight avenues for enhancing STEM participation for students with disabilities, offer suggestions for improvements to future data collection efforts, and lend guidance for future researchers looking to study disability using the HSLS:09 or other secondary data.

vii TABLE OF CONTENTS Page ACKNOWLEDGMENTS. vi LIST OF TABLES. xii LIST OF FIGURES .1 Disability as Diversity. 4 Enhancing the Workforce through STEM Education.

8 High School Data to Study the STEM Pipeline. 12 Choosing the Appropriate Metaphor. 13 Purpose of this Dissertation. 16 Chapter Two: Disability in Education Research Using National Datasets: Definition and Measurement Considerations.

16 Chapter Three: Influence of STEM Valuation and Success Expectations on Major Declaration for Students with Disabilities. 17 Chapter Four: Influence of Multiple Forms of Capital on STEM Major Intentions for Students with Disabilities. DISABILITY IN EDUCATION RESEARCH USING NATIONAL DATASETS: DEFINITION AND MEASUREMENT CONSIDERATIONS .20 Models of Disability. 24 Categories of Definitions.

24 Scope of Definitions. 25 Sources of Definitions. 28 Approaches to Measurement. 29 Effects of Operationalization.

30 Survey Research Methods. 32 Assessing HSLS:09 Measures of Disability. 33 Source of Data. 33 Approach to Considering Validity.

35 viii Questions about Conditions. 35 Questions about Difficulty. 39 Troublesome Amount of Missing Data. 42 How Valid were these Data?.

43 Discussion and Implications. 44 Move Away from the Medical Model. 45 Avoid Conceptual Overlap. 46 Allow Self-Identification of Disability.

46 Ask One Question at a Time. 48 Prioritize Collecting Complete Disability Data. 49 Include Additional Measures. INFLUENCE OF STEM VALUATION AND SUCCESS EXPECTATIONS ON MAJOR DECLARATION FOR STUDENTS WITH DISABILITIES.

55 Expectancy-Value Model. 57 STEM Education and Declaring a College Major. 57 Underrepresented Populations in STEM. 59 Students with Disabilities Pursuing STEM.

64 Subjective Task Value and Expectations for Success Variables. 67 Modeling Major Declaration Intention. 74 Expectancy-Value Factor Comparisons. 75 Predicting STEM Majoring for Students with Disabilities.

81 Reliability of Expectancy-Value Factors. 81 Comparisons of Expectancy-Value Factors. 83 ix Expectancy-Value Factors and STEM Major Intentions. INFLUENCE OF MULTIPLE FORMS OF CAPITAL ON STEM MAJOR INTENTIONS FOR STUDENTS WITH DISABILITIES .90 Sources of Capital.

94 Course-Taking and Achievement. 95 Interest in STEM Subjects. 97 STEM Classroom Experiences. 98 STEM for Students with Disabilities.

111 Demographic and Outcome Comparisons. 112 Predicting STEM Majoring for Students with Disabilities. 118 Sources of Capital across Disability Types. 118 Influence of Forms of Capital on STEM Intentions.

119 Influence of School Characteristics on STEM Intentions. DISCUSSION, RECOMMENDATIONS, AND IMPLICATIONS .126 Individual Chapter Review. 128 Chapter Two: Disability in Education Research Using National Datasets: Definition and Measurement Considerations. 128 Chapter Three: Influence of STEM Valuation and Success Expectations on Major Declaration for Students with Disabilities.

129 Chapter Four: Influence of Multiple Forms of Capital on STEM Major Intentions for Students with Disabilities. 131 x Connected Takeaways and Implications. 133 Takeaway One: Disability Measurement in National Surveys is Problematic. 134 Takeaway Two: Benefits of Using Multiple Disability Identity Categories.

136 Takeaway Three: Benefit of Including Interaction Effects. 138 Takeaway Four: Students with ADHD More Likely to Pursue STEM. 139 Next Steps for Disability Research. 140 Next Step One: Expand Disability Definition Critique.

140 Next Step Two: National Discussion about Disability Measurement. 142 Next Step Three: Model Psychological and Structural Components Together. 143 Next Step Four: Repeat Models with Data from Two Time Points Simultaneously.147 xi LIST OF TABLES Table Page Table 1. Question Text for Binary Measures from Parent Survey.

Question Text for Difficulty Measures from Parent Survey. Parental Report of Specific Conditions by Receipt of Special Education Services. Parental Report of Specific Conditions by Receipt of IEP. Scale Question Text, Response Options, and Alpha Coefficients.

Descriptive Comparison Differences across Disability Typesa. STEM Major Declaration Intention Model with Background Characteristics, Odds Ratios. STEM Major Declaration Intention Model with Background Characteristics and Expectancy-Values, Odds Ratios. STEM Major Declaration Intention Model with Background Characteristics, Expectancy-Values, and Interaction Effects, Odds Ratios.

Descriptive Comparison Differences across Disability Typesa. STEM Major Declaration Intention with Demographic Characteristics, Odds Ratios. STEM Major Declaration Intention with Demographic Characteristics, Sources of Capital, and Interactions, Odds Ratios. 117 xii LIST OF FIGURES Figure Page Figure 1.

The Leaky STEM Pipeline. International Classification of Functioning, Disability, and Health. Conceptual Model of STEM Major Declaration. Revised Conceptual Model of STEM Major Declaration.

118 xiii CHAPTER 1 INTRODUCTION Recent postsecondary enrollment trends demonstrate positive growth for the population of students with disabilities. Estimates place the percentage of college students with disabilities around 11 to 12 percent (Snyder & Dillow, 2013; Snyder, de Brey, & Dillow, 2016), up from approximately 5 percent in 2000 (Snyder & Hoffman, 2001). The growth is likely due in large part to federal legislation allowing and protecting access to postsecondary education for these students. Section 504 of the Rehabilitation Act of 1973 established a federal mandate that persons with disabilities be allowed to attend postsecondary institutions (Peña, 2014).

Accessibility was further enhanced following the passage of the Americans with Disabilities Act of 1990, providing additional civil rights protections for this population (Evans & Herriott, 2009; U. Government Accountability Office, 2009). However, some have called these figures into question. The Higher Education Research Institute (2011) estimated the figure to be closer to 15 percent of full-time, first- year students having at least one disability.

Subpopulation estimates of students with different types of disabilities also fluctuate depending on the data source used. Leake (2015) noted the discrepancies between the National Postsecondary Student Aid Study of 2008 (NPSAS:08) and the National Longitudinal Transition Study 2 (NLTS-2) estimates in identifying the percentage of students with different types of disabilities. Notably, the NPSAS:08 results showed that fewer than 10 percent of students with disabilities 1 identified as having a learning disability; however, the NLTS-2 found that almost 70 percent of students with disabilities had a learning disability. Leake (2015) suggested that the difference between the results could be attributable to the different classifications used by each survey.

The NLTS-2 used categories from the Individuals with Disabilities Education Act (IDEA), while the NPSAS:08 categories were based on the Americans with Disabilities Act (ADA). Adding support to Leake’s argument, a study focusing on hearing impairments identified a range of estimates from as low as 25,000 to upwards of 400,000 (Schroedel, 2007). With such discrepancies being identified, there are considerable implications for disability researchers. Depending on the source of data used, rates of disability are likely to vary.

Differences between surveys are driven by inconsistent definitions, which also lead to different types of disability being represented in research. To further unpack this issue, defining disability is discussed later in this chapter and emphasized in Chapter Two. While the exact percentage of students with disabilities who proceed from high school to some form of postsecondary education is debated, the increase in the number of students following this path is desirable because college has been increasingly shown to result in positive earnings outcomes for everyone. Workers holding a four-year degree are poised to earn 84 percent more in their lifetimes than workers with only high school credentials (Carnevale, Rose, & Cheah, 2011).

The majority of jobs already require some form of postsecondary education, and the percentage is expected to continue to rise (Carnevale, Smith, & Strohl, 2010). Employment outcomes for individuals with disabilities are troubling and perhaps the increased postsecondary enrollment of this population will help correct current inequities. Persons with disabilities have an 2 unemployment rate twice as high (Bureau of Labor Statistics, 2017) and have lower monthly median incomes than individuals without disabilities (Brault, 2012). Efforts to increase employment for this population are critical in order to help foster upward mobility.

This unemployment trend extends to science, technology, engineering, and math (STEM) careers, a discrepancy that emerges from differences in the pursuit and completion of related majors during postsecondary education (National Science Foundation [NSF], 2015). Limited research suggests that students with disabilities entering postsecondary education declare STEM-related majors at a similar rate as their peers without disabilities (Lee, 2011).