Supporting Instructional Sense-Making Through Early Engagement Clustering in Online Professional Learning

• In Event: Elements of Instructional Design in Online Settings

Abstract

In online professional learning (OPL), facilitators often struggle to identify disengaged learners due to limited interaction and time. This study analyzes first-week engagement data from a 4-week asynchronous literacy endorsement program, using the Immediacy, Frequency, and Duration (IFD) framework and pre-assessment scores to cluster learners. K-means analysis reveals distinct profiles with significant differences in completion rates. Instead of complex dashboards, the study offers light-touch, interpretable summaries to support instructors’ decision-making. These findings lay the groundwork for scalable, human-in-the-loop learning analytics that center educator judgment in resource-constrained environments.

Author

• Sophia Soomin Lee, University of Florida