ABSTRACT Rochelle R. Newton, MASSIVE OPEN ONLINE COURSES AND COMPLETION RATES: DOES ACADEMIC READINESS AND ITS FACTORS INFLUENCE COMPLETION RATES IN MOOCS? (Under the direction of Dr. Crystal Chambers). Department of Educational Leadership, November 2016. With the increase in the cost of an education and the flat employment rate, many institutions and students are looking to online learning to solve this academic dilemma. Online education is thought to be a low-cost academic alternative to brick and mortar courses. Massive Open Online Courses (MOOCs) goals include issues of equity in higher education, the rising costs of a college education, and funding concerns. MOOCs can be taken from anywhere as long as the participant has a computer and access to the Internet is available. Also, traditional MOOCs do not require any financial commitment and do not have academic prerequisites or an admissions process. Completion rates among learners taking MOOCs are low, begging the question of whether they actually address matters of escalating college costs and higher education equity. The purpose of this study is to explore whether academic readiness in the context of the likelihood the learner completing the course. This study focuses on one component of the many factors in MOOCs - the likelihood of course completion and academic readiness. Academic readiness in MOOCs is not a requirement, but a component that may determine whether a learner has the tools needed to complete a MOOC. Academic readiness suggests a level of knowledge and cognitive abilities necessary to understand the course content and to navigate the course technologically. Theories addressing structural elements within MOOCs include Clow’s funnel of participation, behaviorism, and constructivism. Of these theories, constructivism provides the theoretical framework for understanding learners’ abilities and willingness to learn in the study. This quantitative study attempts to evaluate the likelihood of course completion and the factors that may influence these outcomes using secondary data from Duke’s MOOC pre- and post-course surveys. Logistic regression analysis with the dependent variable (a learner completes a Duke’s MOOCs) and the independent variables (academic readiness and its factors – college degree; age; race; gender; previous experience with course subject, course level – beginner, intermediate; or advanced; and STEM or non-STEM) will be used to estimate the likelihood that these variables will encourage learners to complete MOOCs or understand why learners do not. MASSIVE OPEN ONLINE COURSES AND COMPLETION RATES: DOES ACADEMIC READINESS AND ITS FACTORS INFLUENCE COMPLETION RATES IN MOOCS? A Dissertation Presented to The Faculty of the Department of Educational Leadership East Carolina University In Partial Fulfillment of the Requirements for the Degree Doctor of Education in Educational Leadership by Rochelle Newton November, 2016 ©Copyright 2016 Rochelle Newton MASSIVE OPEN ONLINE COURSES AND COMPLETION RATES: DOES ACADEMIC READINESS AND ITS FACTORS INFLUENCE COMPLETION RATES IN MOOCS? by Rochelle Newton APPROVED BY: DIRECTOR OF DISSERTATION:___________________________________________ Crystal Chambers, PhD COMMITTEE MEMBER:__________________________________________________ Kathy Lohr, EdD COMMITTEE MEMBER:__________________________________________________ Xiangming Fang, PhD COMMITTEE MEMBER:__________________________________________________ Kim Manturuk, PhD CHAIR OF THE DEPARTMENT OF EDUCATIONAL LEADERSHIP: ___________________________________________________ William Rouse, Jr., EdD DEAN OF THE GRADUATE SCHOOL: ___________________________________________________ Paul Gemperline, PhD ACKNOWLEDGEMENTS I must gracefully thank my family who allowed me to lock myself in my room to read and write. My seventeen-year-old son, Everett, often came into my bedroom to check on me and remarked that he was proud of me. This encouragement pushed me forward to be an example for him and his future. My husband, Skip, allowed me the space to write. My daughter, Dechelle, often called or texted from her home in Washington, DC to encourage me to push through when I felt lost or felt like giving up. Many of my classmates from earlier education reached out to share their thoughts about their acknowledgment of my endeavor. Achieving this degree was not without its challenges, and I owe a debt of gratitude to my instructors at East Carolina. Dr. Crystal Chambers, my dissertation chair, has been with me since day one and was a constant force of support and reinforcement that I could complete this degree. She saw what was possible for me when I did not. I would not be here without her. I would also like to acknowledge Dr. David Siegel for his wisdom and kindness. I must thank the entire East Carolina staff and professors for their leadership and support. My dissertation committee has been a joy and been there through each turn. I thank my entire ECU 2012 cohort. I would also like to thank Guangya Liu for educating and explaining logistic regression to me. Lastly, I thank Duke University for making this degree possible. My managers, Wayne Miller, and Richard Danner, supported me, as an employee, in every manner possible. They allowed me to intern, research, and write while still performing my duties and responsibilities. Thank you, Kyle Cavanaugh, for unwavering support and encouragement. TABLE OF CONTENTS Page TITLE………………………………………………………………………………….. i COPYRIGHT………………………………………………………………………..... ii SIGNATURE…………………………………………………………………………. iii ACKNOWLEDGEMENTS…………………………………………………………... iv LIST OF TABLES…………………………………………………………………..... ix CHAPTER 1: INTRODUCTION……………………………………………………. 1 Background of the Study…………………………………………………….. 2 Statement of the Problem…………………………………………………… 6 Central Research Questions………………………………………………… 7 Overview of the Methodology……………………………………………….. 9 Limitations and Assumptions of the Study………………………………… 10 Theoretical Framework…………………………………………………….... 11 Importance of the Study……………………………………………………... 13 Definition of Terms…………………………………………………………… 16 Organization of the Study……………………………………………………. 24 CHAPTER 2: REVIEW OF LITERATURE………………………………………… 26 Background…………………………………………………………………… 26 Online Education: An Overview…………………………………………...... 26 Massive Open Online Courses (MOOCs)………………………………..... 29 What is a MOOC?.................................................................................... 31 MOOC Types: Connectivist and Extended MOOCs…………………....... 39 Connectivist MOOCs (cMOOCs)…………………………………..... 41 Extended MOOCs (xMOOCs)……………………………………….. 43 The Business of Higher Education, Retention, and MOOCs……………. 49 Learning Theories in MOOCs……………………………………………….. 58 Behaviorism Theory…………………………………………………... 60 Constructivism Theory………………………………………………... 61 Constructivist Theory and the Community of Inquiry……………… 63 Learning in MOOCs………………………………………………………….. 66 The Role of the Instructor……………………………………………………. 68 MOOCs and Diversity………………………………………………………... 69 The Potential Impact of MOOCs…………………………………………..... 72 The Challenge of Course Completions in MOOCs……………………….. 76 Academic Readiness………………………………………………………… 84 Learner Age and Experience………………………………………………... 90 Course Factors……………………………………………………………….. 92 Gender and Race…………………………………………………………….. 94 Science, Technology, Engineering, and Math (STEM)…………………... 95 Readiness and Science, Technology, Engineering, and Math (STEM)... 97 Chapter 2 Summary………………………………………………………….. 98 CHAPTER 3: METHODOLOGY……………………………………………………. 101 Overview of the Research Methods………………………………………... 101 Site Selection………………………………………………………………..... 101 Duke’s Coursera Data……………………………………………………….. 103 Responses…………………………………………………………………….. 104 Variables……………………………………………………………………..... 107 Dependent Variable…………………………………………………... 108 Independent Variable…………………………………………………. 108 Data Analysis and Method…………………………………………………... 112 Limitations of the Study……………………………………………………… 114 Chapter 3 Summary………………………………………………………….. 116 CHAPTER 4: RESULTS…………………………………………………………..... 118 Central Research Question…………………………………………………. 118 Dependent Variable – Whether Learners Complete a MOOC………….. 119 Independent Variables……………………………………………………….. 125 Bivariate Analysis…………………………………….……………….. 127 Logistic Regression Analysis………………………………………… 128 Chapter 4 Summary…………………………………………………………. 129 CHAPTER 5: SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS….. 131 Background…………………………………………………………………… 131 Science, Technology, Engineering, and Math (STEM) and Level of Academic Challenge…………………………………………………………. 133 Prior Experience in Online Education……………………………………… 135 MOOCs and Diversity………………………………………………………... 135 The Potential Impact of MOOCs…………………………………………..... 139 The Challenge of Course Completions…………………………………….. 148 Academic Readiness………………………………………………………… 148 Learner Age and Experience………………………………………………... 150 Implications of the Study…………………………………………………...... 151 Recommendations for Higher Education and MOOC Providers………… 154 Recommendations for Higher Education…………………………………... 155 Recommendations for Future Research…………………………………… 156 Limitations of the Research………………………………………………..... 158 Conclusion…………………………………………………………………….. 159 REFERENCES………………………………………………………………………. 162 APPENDIX A: PRE-COURSE SURVEY………………………………………...... 212 APPENDIX B: POST-COURSE SURVEY………………………………………… 229 APPENDIX C: DUKE IRB APPROVAL………………………………………….... 239 APPENDIX D: ECU IRB APPROVAL……………………………………………… 240 LIST OF TABLES 1. MOOC Completion Rates by Providers……………………………………...... 5 2. MOOC Variants…...……………………………………………………………..