While predicting completion in Massive Open Online Courses (MOOCs) has been an active area of research in recent years, predicting completion in self-paced MOOCS, the fastest growing segment of open online courses, has largely been ignored. Using learning analytics and educational data mining techniques, this study examined data generated by over 4,600 individuals working in a self-paced, open enrollment college algebra MOOC over a period of eight months.
Download count: 0
- Partial requirement for: Ph.D., Arizona State University, 2017Note typethesis
- Includes bibliographical references (pages 98-115)Note typebibliography
- Field of study: Educational technology