Investigating Self-Regulated Learning Prompts Using Learning Analytics

• In Event: 66.066 - Understanding Patterns, Visuals, and Changes

Abstract

Self-regulated learning is considered to be crucial for successful learning. However, students often do not show such strategies spontaneously. Prompts can be applied as instructional means to elicit latent strategies. Hence, this quasi-experimental study investigates the impact of prompts related to self-regulated learning on declarative knowledge including trace data at an initial level (note taking during learning, interaction with the learning environment). Findings indicate no significant differences of the prompting conditions on learning performance nor did the trace data predict learning outcomes, whereas learner characteristics were significant predictors. Future research should integrate additional trace data over a longer period of time to better identify patterns of learning processes and how interventions may help to personalize learning experiences.

Authors

• Clara Schumacher, University of Mannheim

• Dirk Ifenthaler, University of Mannheim