Exploring Demographics and Students' Motivation as Predictors of Completion of a Massive Open Online Course

Qing Zhang, Fernanda Cesar Bonafini, Barbara B. Lockee, Kathryn W. Jablokow, Xiaoyong Hu

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


This paper investigates the degree to which different variables affect the completion of a Massive Open Online Course (MOOC). Data on those variables, such as age, gender, English proficiency, education level, and motivation for course enrollment were first collected through a pre-course survey. Next, course completion records were collected via the Coursera database. Finally, multiple binomial logistic regression models were used to identify factors related to MOOC completion. Although students were grouped according to their preferences, working in groups did not affect students' likelihood for MOOC completion. Also, other variables such as age, the institution hosting the MOOC, academic program alignment with students' needs, and students' intention to complete the course all affected their probability of MOOC completion. This study contributes to the literature by indicating the factors that influence the probability of MOOC completion. Results show that older participants (age > 50 years old) have higher probability of completing the MOOC. Students' MOOC completion also increases when the MOOC provides experiences that add to students' current academic backgrounds and when they are hosted by institutions with a strong academic reputation. Based on these factors, this study contributes to research methods in MOOCs by proposing a model that is aligned with the most important factors predicting completion as recommended by the current MOOC literature. For the next phase of assigning learners to work in groups, findings from this study also suggest that MOOC instructors should provide assistance for group work and monitor students' collaborative processes.

Original languageEnglish (US)
Pages (from-to)140-161
Number of pages22
JournalInternational Review of Research in Open and Distance Learning
Issue number2
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Education


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