Modeling self-efficacy in intelligent tutoring systems: An inductive approach
User Modeling and User-Adapted Interaction
Modeling Task-Based vs. Affect-based Feedback Behavior in Pedagogical Agents: An Inductive Approach
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Encouraging students to study more: adapting feedback to personality and affective state
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Encouraging students to study more: adapting feedback to personality and affective state
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
The quest for validated personality trait stories
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Adapting performance feedback to a learner's conscientiousness
UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization
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This study aims to establish how tutors adapt to Generalised Self-Efficacy when providing feedback on progress to a learner. Tutors seem to adapt to learners with low self-efficacy, providing a positive slant to topics on which the learner performed very badly. Results can be used by a conversational agent to adapt feedback to learners' self-efficacy.