Dynamics of affective states during complex learning
Learning and Instruction Volume 22, Number 2, ISSN 0959-4752 Publisher: Elsevier Ltd
We propose a model to explain the dynamics of affective states that emerge during deep learning activities. The model predicts that learners in a state of engagement/flow will experience cognitive disequilibrium and confusion when they face contradictions, incongruities, anomalies, obstacles to goals, and other impasses. Learners revert into the engaged/flow state if equilibrium is restored through thought, reflection, and problem solving. However, failure to restore equilibrium as well as obstacles that block goals trigger frustration, which, if unresolved, will eventually lead to boredom. The major hypotheses of the model were supported in two studies in which participants completed a 32–35min tutoring session with a computer tutor. Their affective states were tracked at approximately 110 points in their tutoring sessions via a retrospective affect judgment protocol. Time series analyses confirmed the presence of confusion–engagement/flow, boredom–frustration, and confusion–frustration oscillations. We discuss enhancements of the model to address individual differences and pedagogical and motivational strategies that are inspired by the model.
D’Mello, S. & Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2), 145-157. Elsevier Ltd.
Cited ByView References & Citations Map
J. Elizabeth Richey, Carnegie Mellon University, United States; Juan Miguel L. Andres-Bray, University of Pennsylvania, United States; Michael Mogessie, Carnegie Mellon University, United States; Richard Scruggs & Juliana M.A.L. Andres, University of Pennsylvania, United States; Jon R. Star, Harvard University, United States; Ryan S. Baker, University of Pennsylvania, United States; Bruce M. McLaren, Carnegie Mellon University, United States
Computers & Education Vol. 139, No. 1 (October 2019) pp. 173–190
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