Dual-Credit Access, Participation and Outcomes in Washington State Ashley Birkeland A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2019 Reading Committee: Margaret L. Plecki, Chair Elizabeth A. Sanders Ana M. Elfers Program Authorized to Offer Degree: College of Education i ©Copyright 2019 Ashley Birkeland ii University of Washington ABSTRACT Dual-Credit Access, Participation and Outcomes in Washington State Ashley Birkeland Chair of the Supervisory Committee: Professor Margaret L. Plecki College of Education Dual-credit has become a prominent topic in education as states look for additional opportunities to prepare students to succeed in college. Research has shown that students who earn college credit in high school are more likely to enroll in college. In Washington, there is currently a policy in place to increase enrollment in dual-credit courses. In addition, the Every Student Succeeds Act (ESSA) has given states more flexibility in how they are held accountable and Washington is one of the states that adopted dual-credit participation as an accountability measure. This study is informed by the results of a previous pilot study and includes all six dual- credit programs offered in Washington state. The six programs are AP, Cambridge, College in the High School, IB, Running Start and Tech Prep. Both descriptive and predictive approaches are taken to answer the questions 1) who has access and participates in different dual-credit programs, and 2) does dual-credit participation predict high school graduation and college enrollment after controlling for demographics and GPA? The results of this study provide a more nuanced picture of dual-credit access in Washington when only basic statistics at the state level have been produced thus far. Tech Prep has the highest participation rate, and Cambridge the lowest. Students from outside the greater Puget Sound area have access to fewer dual-credit options and have lower participation rates. Students from smaller districts are also less likely to participate in dual-credit but have higher participation in Running Start compared to larger districts. Results from the predictive Hierarchical Linear Models show that AP, Running Start and College in the High School are all significant predictors of any college enrollment. Running Start participation is associated with an increased probability of any college enrollment for underrepresented minority students and College in the High School participation is associated with an increased probability of any college enrollment for students who are English language learners. Implications for policy and future research are discussed. Keywords: Dual-credit, access, participation, graduation, college enrollment iii ACKNOWLEDGMENTS The completion of my doctoral program and dissertation would not have been possible without all the guidance and support I received along the way. There were many times when this work felt impossible and there are so many people that kept me going. To my advisor, Marge Plecki, thank you for your constant encouragement and guidance throughout this process. This wouldn’t have been possible without those weekly calls and expectations. To Liz Sanders, you have been around for all of my graduate education and have been a source of inspiration and knowledge. Thank you for leading me to Marge and always being available along the way. Ana Elfers, I truly appreciate the time you spent as my interim advisor during my early years in the program, your positivity made it easier to keep pushing on. And to Mark Long, thank you for your methodological feedback and always bringing me back to the research. To my former and current work colleagues thank you for listening to my research ideas and being the first to listen to my presentations and give feedback. And to my past and current supervisors, thank you for your support and encouragement along the way. Balancing work and school is never easy, but you always made me feel like I made the right decision. Last and certainly not least, I have to extend the biggest thank you to my family for their enduring support while I was on this doctoral program journey. Thank you for always checking in and telling me I could do it. Mom and Dad, anytime I have big plans like this you support them and wait for me to complete them, because you just know I will. Thank you for your never- ending support. To my husband Paul, there were so many times when I wondered what I was doing and if I could really complete this program and your belief in me never waivered. Thank you for going above and beyond and helping to get me through. And to Tavin, you are the best thing that happened to me along this journey. You made my experience different and ultimately better these last couple years and were a source of motivation to finish what I started. iv TABLE OF CONTENTS Chapter 1: Introduction………………………………………………………………….…… 1 1.1 Rationale and Focus of the Research………………………………………………….……. 1 1.2 Research Questions…………………………………………………………………….…… 3 Chapter 2: Literature Review………………………………………………………………… 4 2.1 Dual-credit definitions………………………………………………………………………. 4 2.2 Current dual-credit programs and how they differ………………………………………….. 6 2.3 Purpose of dual-credit and change over time……………………………………………….. 10 2.4 Who takes dual-credit courses?.............................................................................................. 13 2.5 Definition of dual-credit success and effects at the organizational and student level……… 14 2.6 Popular research designs……………………………………………………………………. 18 2.7 Knowledge Gaps……………………………………………………………………………. 20 2.8 Significance…………………………………………………………………………………. 21 Chapter 3: Research Design and Methodology……………………………………………… 23 3.1 Conceptual Framework…………………………………………………………………..…. 23 3.2 Methods……………………………………………………………………………………... 26 3.3 Sample………………………………………………………………………………………. 26 3.4 Data Analysis Strategy……………………………………………………………………… 27 3.5 Measures……………………………………………………………………………………. 28 3.6 Data Cleaning…………………………………………………………………….…………. 32 Chapter 4: Descriptive Analysis Results………………………………………….………….. 33 4.1 Overall Sample........................................................................................................................ 33 4.2 Dual-Credit Overall………………………………………………………………………… 36 4.3 Tech Prep Analysis…………………………………………………………………………. 37 4.4 Advanced Placement Analysis……………………………………………………………… 39 4.5 Running Start Analysis…………………………………………………………………...… 41 4.6 College in the High School Analysis……………………………………………………….. 45 4.7 International Baccalaureate Analysis……………………………………………………….. 47 v 4.8 Cambridge Analysis………………………………………………………………………… 49 4.9 Any Dual-Credit Analysis…………………………………………………………………... 51 4.10 Dual-Credit by ESD and District Size…………………………………………………….. 53 4.11 Dual-Credit by District and School Wealth……………………………………………….. 57 4.12 Descriptive Analysis Discussion…………………………………………………………... 59 Chapter 5: Predictive Analysis Results………………………………………………………. 61 5.1 HLM Overview……………………………………………………………………………... 61 5.2 HLM Initial Analyses………………………………………………………………………. 62 5.3 HLM Final Models…………………………………………………………………………. 63 5.4 Tech Prep…………………………………………………………………………………… 69 5.5 AP………………………………………………………………………………………...… 72 5.6 Running Start……………………………………………………………………………….. 76 5.7 College in the High School…………………………………………………………………. 81 5.8 Predictive Analysis Discussion……………………………………………………………... 86 Chapter 6: Discussion and Implications…………………………………………………...… 90 6.1 Summary of Key Findings………………………………………………………………….. 90 6.2 Challenge of Inequitable Access……………………………………………………………. 91 6.3 Implications…………………………………………………………………………………. 94 6.4 Limitations and Suggestions for Further Research…………………………………………. 96 Appendices………………………………………………………………….……………....... 104 Appendix A. Locations of Washington IB Programs……………….………………………... 104 Appendix B. Dual-Credit Participation by District Size……………………….……………... 105 Appendix C. Zero-Order Correlations………………………………………….…………….. 106 Appendix D. HLM 3 and 4 Level Model Results……………………………...……...…. 107-108 Appendix E. HLM Direct and Unique Effects Models………..…………………….…… 109-112 Appendix F. HLM First Version Full Models……………………………..………………….. 113 vi LIST OF TABLES Chapter 4 Table 1. Demographics for Overall Sample……………………………….…………………… 33 Table 2. Demographics by ESD……………………………………………...……...………….. 35 Table 3. Sample by Region…………………………………………………...……...…………. 36 Table 4. Dual-Credit Participation……………………………………………………………... 37 Table 5. Demographics for Overall Sample and Tech Prep……………………………………. 38 Table 6. Demographics for Overall Sample and AP…………………………………………… 41 Table 7. Demographics Overall Sample and for Running Start…………………………...…… 43 Table 8. Demographics for Overall Sample and CHS………………………………………….. 46 Table 9. Demographics for Overall Sample and IB…………………………………………….. 48 Table 10. Demographics for Overall Sample and Cambridge………………………………..… 50 Table 11. Demographics for Overall Sample and Any Dual-Credit……………………………. 51 Table 12. Demographics for Overall Sample, Any DC and Any DC No TP……………….….. 52 Table 13. Comparison of Dual-Credit Participation Rates Within Program……….……..……. 53 Table 14. Dual-Credit by ESD…………………………………………………….……………. 54 Chapter 5 Table 15. Sample by Outcome…………………………….…………………………………….61 Table 16. Tech Prep HLM Results………………………….………………………………….. 65 Table 17. AP HLM Results………………………………….…………………………………. 66 Table 18. Running Start HLM Results……………………….………………………………… 67 Table 19.