Using Learning Analytics Approach to Inform Interventions for Improving Self-Regulated Learning and Higher-Order Thinking: A Pilot Study

• In Event: Online Support
  In Roundtable Session: Systems Thinking in Higher Education

Short Description

This session discusses a study that assessed how grounding the data-informed interventions in Blooms’ mastery learning influenced students’ self-regulated learning (SRL) and higher-order thinking skills (HOTS). Two engineering course sections were randomly assigned to either control group (CG) or treatment group (TG). Analytics tools were used in TG to analyze learning progress and inform decisions on appropriate interventions. Pre- and post-survey results indicated changes in SRL and HOTS were overall found more positive in TG.

Authors

• Presenter: Pauline Salim Muljana, Old Dominion University

• Presenter: Tian Luo, Old Dominion University

• Contributor: Greg Placencia, California State Polytechnic University, Pomona