Understanding Learners Behavior in Massive Open Online Courses

Massive Open Online Courses (MOOCs) are one of the most disruptive trends of recent years, attracting millions of students around the world. This has caught the attention of researchers who seek to understand the behavior of students in these courses. However, despite the efforts, approval rates remain below 5%, so more efforts are needed to understand why students end a MOOC or not. The goal of this work is to study learner's behavior in a MOOC. Specifically, it seeks to understand student interaction sequences with course resources and characterize their study sessions throughout MOOC weeks. For this, using Process Mining techniques, data from N = 38,838 learners enrolled in a MOOC in Coursera were analyzed. As a result of the analysis of learner's interactions with MOOCs, two groups of students were observed as comprehensive and strategic. In addition, differences in learning sequences were found among students from both groups who approved the MOOC. These results help advance current literature and open the debate about whether MOOCs remain open courses or a digital book.