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Communication Dans Un Congrès Année : 2016

The role of an open learner model and immediate feedback on metacognitive calibration in MetaTutor

Reza Feyzi-Behnagh
  • Fonction : Auteur
Roger Azevedo
  • Fonction : Auteur
Yan Tian
  • Fonction : Auteur

Résumé

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 out comes pre-to-posttest, with no difference between with-feedback and no-feedback conditions.
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Dates et versions

hal-01340594 , version 1 (01-07-2016)

Identifiants

  • HAL Id : hal-01340594 , version 1

Citer

Reza Feyzi-Behnagh, Roger Azevedo, François Bouchet, Yan Tian. The role of an open learner model and immediate feedback on metacognitive calibration in MetaTutor. The 2016 Annual meeting of the American Educational Research Association, Apr 2016, Washington, DC, United States. ⟨hal-01340594⟩
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