Strategic and Comprehensive: Modeling MOOC Learner Behavior Through Process Mining of Learning Sequences

This exploratory study analyzes student behavior in a Massive Open Online Course (MOOC). MOOCs represent a global educational phenomenon transforming teaching and inspiring new research perspectives on learning methods in higher education institutions. Understanding how students organize their learning sequences and how these relate to their academic performance is crucial for optimizing digital educational processes. The objective of this study is to identify and characterize the learning sequences performed by students during their study sessions in a MOOC, using process mining (PM) techniques. The methodology involved analyzing a dataset collected between July 2017 and January 2018, comprising 27,922 students and approximately 3.5 million recorded interactions. Process mining techniques were employed to examine these learning sequences. Results indicate that most interactions correspond to assessments and video lectures, while forums were the least utilized activity. Additionally, two student profiles were identified: “Comprehensive” learners, who follow expected sequences and engage in longer, more intensive study sessions, and “Strategic” learners, who prioritize assessments. This study advances the current understanding of online learning and situates its findings within the broader literature by contrasting them with similar classification patterns reported by other authors.