Motivations Matter: Predicting Entrepreneurship Education MOOC Course Completion with a Decision Tree Approach

Online entrepreneurship education (EE) courses experienced a sharp 66% spike in demand around March 2020, attributed to the COVID-19 pandemic and the subsequent surge in digital entrepreneurship uptake. Completion rates serve as a key indicator of online MOOC efficacy, with students’ psychological attributes and contextual factors often examined as explanatory variables in assessing online course completion. This mixed-methods study explores influential factors in student retention in an EE Massive Open Online Course (MOOC) by using survey responses from 222 Malaysian youths who voluntarily registered for an EE MOOC, which was active from February to October 2021. A Decision Tree approach was chosen to predict the course completion likelihood based on sociodemographic and psychological factors, while qualitative content analysis was conducted to explore participant course enrollment motivations from their textual responses. The results indicated that entrepreneurial intention (EI) does not necessarily translate into EE MOOC completion. Instead, internal locus of control and socioeconomic factors held more priority in predicting completion status. These results were reflected in the students’ thematic narratives from their textual responses. Both completed (CP) and dropout participants (DP) expressed similar entrepreneurial interests and, indeed, in the transferability of entrepreneurial skills and knowledge beyond entrepreneurial settings. However, there was a distinction in clarity; most CPs had well-defined and detailed enrolment goals, whereas the narratives from DPs were mainly ambiguous. Overall, the study contributes to the methodological discussion of using decision tree modelling, expands the application of Social Cognitive Career Theory (SCCT) and informs practical implications in online EE context.