Using Educational Data Mining to Explore Time Dimensions of Participation in Online Learning

• In Event: Online Learning Perspectives and Approaches

Abstract

Learning and participation are inseparable in the online learning environment. Much effort has been invested in encouraging online participation, but the effort tends to view online participation as a numerically aggregated variable, overlooking time issues of participation. Learning is a series of cumulative events, so participation at different stages are of variant significance. Several pivotal moments may determine different participation patterns. This research thus investigates online learners’ longitudinal trajectory of participation using educational data mining techniques. Time dimensions of participation are validated as more accurate measures to distinguish online learners’ performance. Further, design and pedagogical implications are provided for educators to help learners maintain active participation. For example, educators might provide early scaffolds to encourage learner participation in online courses.

Authors

• Hengtao Tang, The Pennsylvania State University

• Wanli Xing, Texas Tech University