Examining the predictive relationship between personality and emotion traits and students' agent-directed emotions: towards emotionally-adaptive agent-based learning environments
| Autor: | Cassia K. Carter, Ronald S. Landis, Lana Karabachian, Roger Azevedo, Niki Papaionnou, François Bouchet, Jason M. Harley |
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| Přispěvatelé: | Modèles et Outils en ingénierie des Connaissances pour l'Apprentissage Humain (MOCAH), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Agreeableness
Pedagogical Agents Computer science media_common.quotation_subject Emotions 02 engineering and technology Trait Emotions Education 0202 electrical engineering electronic engineering information engineering medicine Personality Agent-directed Emotions Big Five personality traits media_common Personality Traits 4. Education Learning environment 05 social sciences 050301 education Conscientiousness Boredom Intelligent Tutoring Systems Neuroticism Computer Science Applications Human-Computer Interaction Adaptivity [SCCO.PSYC]Cognitive science/Psychology Trait 020201 artificial intelligence & image processing [INFO.EIAH]Computer Science [cs]/Technology for Human Learning medicine.symptom 0503 education Cognitive psychology |
| Zdroj: | User Modeling and User-Adapted Interaction User Modeling and User-Adapted Interaction, Springer Verlag, 2016, 26 (2), pp.177-219. ⟨10.1007/s11257-016-9169-7⟩ User Modeling and User-Adapted Interaction, 2016, 26 (2), pp.177-219. ⟨10.1007/s11257-016-9169-7⟩ |
| ISSN: | 0924-1868 1573-1391 |
| DOI: | 10.1007/s11257-016-9169-7⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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