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Université du Québec à Montréal|uqam|



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Analyzing and visualizing the dynamic aspects of affect and cognition across contexts

Learning can be attributed to the cumulative effect of temporally fine-grained affective and cognitive events occurring over longer learning episodes. Optimizing learning efforts, for example by better pedagogical design or by improving learners’ metacognitive skills, requires causal explanations linking learning with cognition and affect in correspondence with the rate of change of those processes. Current research on learning processes is severely limited by incomplete data of learners’ cognitive processes and affective states that are contingent on context-specific factors (e.g., problem complexity, time constraints, situation dynamics, and external regulating agents).

Participants in this symposium are invited to present an empirical study on the theme of “online measures of learning” which could contribute theoretical or methodological advances to an emerging research program oriented towards the concomitant behavioral and psychophysiological modeling of cognitive and affective aspects of learning in increasingly authentic contexts. The four presentations constituting this symposium address this issue by proposing theoretical frameworks, types of data, strategies for data analysis as well as technical tools to analyse and visualize process-oriented data about learning. This collection of work provides new insights regarding the notion that learners interact dynamically with aspects of the learning situation, such as the learning task itself, as well as with other agents such as co-learners or intelligent virtual humans. This fine-grained information will enhance our conceptual and theoretical understanding of learners’ affect and cognition and subsequently provide evidence for optimizing learning across contexts.


Roger Azevedo, Nicholas V. Mudrick, Michelle Taub, Garrett C. Millar, Amanda E. Bradbury, Megan J. Price

Jonna Malmberg, Sanna Järvelä, Ilkka Juuso, Iman Alikhani,  Tapio Seppänen

Inge Molenaar

Julien Mercier, Pierre Chalfoun, Babak Khosravifar, Kamran Shaikh

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