The Intertemporal Impact of Self-Regulation: Analyzing Timing Profiles

• In Event: 43.070 - Self-Directed Learning and Metacognition

Abstract

Learning analytics, and the use of digital learning environment generated trace data in general, has provided new ways in exploring what decisions students design their self-regulated learning. Time-management is a crucial aspect of this. In this large-scale empirical study of 1035 business students who worked on 429 mathematics exercises, using temporal analytics we explored how (self-reported) self-regulated learning was related to how students made learning decisions over time, and how this impacted academic performance.
Using cluster analyses of trace-data in conjunction with three learning disposition instruments, our findings emphasized the role of timing decisions in predicting academic performance. Timely preparation was related to students’ approaches of learning, epistemic learning emotions, and in particular activity learning emotions.

Authors

• Dirk Tempelaar, Maastricht University

• Bart Rienties

• Quan Nguyen, The Open University