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Despite their growing importance, differential, process-oriented research on Massive Open Online Courses (MOOCs) for professional learning is scarce. This paper explores learner behavior in Enterprise MOOCs using lag sequential analysis. Data from 13 MOOCs on business and technology-related topics with a total of N = 72,668 active learners were examined. Starting from consistent high-level behavioral patterns, a deeper analysis reveals variations in interaction sequences according to the underlying course design approach. Lecture-oriented, system interaction-oriented and discussion-oriented courses share a set of common patterns, but also differ in various interaction sequences. Linking interactions to achievement data may uncover promising behavior patterns to be supported by the course design. Based on initial findings, implications for future research and development are drawn.
Marc Egloffstein, University of Mannheim
Presenting Author
Muhittin Sahin, University of Mannheim
Non-Presenting Author
Max Bothe, Hasso Plattner Institute
Non-Presenting Author
Nathanael Schenk, SAP SE
Non-Presenting Author
Florian Schwerer, SAP SE
Non-Presenting Author
Joana Heil, University of Mannheim
Non-Presenting Author
Dirk Ifenthaler, University of Mannheim
Non-Presenting Author