Examining the predictive relationship between personality and emotion traits and students' agent-directed emotions: towards emotionally-adaptive agent-based learning environments

Abstract : The current study examined the relationships between learners’ (N=123) personality traits, the emotions they typically experience while studying (trait studying emotions), and the emotions they reported experiencing as a result of interacting with four pedagogical agents (agent-directed emotions) in MetaTutor, an advanced multi-agent learning environment. Overall, significant relationships between a subset of trait emotions (trait anger, trait anxiety) and personality traits (agreeableness, conscientiousness, and neuroticism) were found for four agent-directed emotions (enjoyment, pride, boredom, and neutral) though the relationships differed between pedagogical agents. These results demonstrate that some trait emotions and personality traits can be used to predict learners’ emotions directed toward specific pedagogical agents (with different roles). Results provide suggestions for adapting pedagogical agents to support learners’ (with certain characteristics; e.g., high in neuroticism or agreeableness) experience of adaptive emotions (e.g., enjoyment) and minimize their experience on non-adaptive emotions (e.g., boredom). Such an approach presents a scalable and easily implementable method for creating emotionally-adaptive, agent-based learning environments, and improving learner-pedagogical agent interactions in order to support learning.
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https://hal.archives-ouvertes.fr/hal-01340595
Contributor : Lip6 Publications <>
Submitted on : Friday, July 1, 2016 - 1:34:59 PM
Last modification on : Tuesday, September 17, 2019 - 10:36:27 AM

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Jason M. Harley, Cassia K. Carter, Niki Papaioannou, François Bouchet, Ronald S. Landis, et al.. Examining the predictive relationship between personality and emotion traits and students' agent-directed emotions: towards emotionally-adaptive agent-based learning environments. User Modeling and User-Adapted Interaction, Springer Verlag, 2016, 26 (2), pp.177-219. ⟨10.1007/s11257-016-9169-7⟩. ⟨hal-01340595⟩

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