The Role of an Open Learner Model and Immediate Feedback on Metacognitive Calibration in MetaTutor

• In Event: Poster Session 13
  In Poster Session: Technology-Based Learning Environments for STEM Education

Abstract

We investigated the calibration of learners’ metacognitive judgments, content page visitation, and study time allocation in the context of learning about the human circulatory system with MetaTutor, a multi-agent hypermedia learning environment. Our participants were 100 college students. Both pedagogical agent (PA) and an open learner model (OLM) were used to provide metacognitive judgment feedback to participants. The results indicated that immediate feedback led to significantly lower over- and underconfidence in participants’ metacognitive judgments and more frequent and longer duration visitations of pages relevant to their current learning sub-goal. The OLM acted as an immediate feedback mechanism for participants who didn’t receive PA’s feedback. All participants achieved significantly higher learning outcomes pre-to-posttest, with no difference between with-feedback and no-feedback conditions.

Authors

• Reza Feyzi Behnagh, University at Albany - SUNY

• Roger Azevedo, North Carolina State University

• François Bouchet, Université Pierre et Marie Curie

• Yan Tian, Albany State University