Course Design Approaches and Behavioral Patterns in Massive Open Online Courses for Professional Learning

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. Results point towards an isolated role of video playbacks across all course clusters, consumerist patterns in lecture-oriented courses, and a positive influence of metacognitively oriented interactions on learning outcomes. Accordingly, initial design recommendations include integrating interactive instructional elements in videos, promoting learner engagement in lecture-oriented courses, and fostering metacognition. Connecting interaction and achievement data may uncover promising behavior patterns that can be further supported by course design. Based on the initial findings, implications for future research and development are discussed.