Prompting, feedback and error correction in the design of a scenario machine
International Journal of Man-Machine Studies
Gender-Specific Approaches to Developing Emotionally Intelligent Learning Companions
IEEE Intelligent Systems
Automatic detection of learner's affect from conversational cues
User Modeling and User-Adapted Interaction
Diagnosing and acting on student affect: the tutor's perspective
User Modeling and User-Adapted Interaction
Investigating Human Tutor Responses to Student Uncertainty for Adaptive System Development
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
What Are You Feeling? Investigating Student Affective States During Expert Human Tutoring Sessions
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Affective Transitions in Narrative-Centered Learning Environments
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
International Journal of Artificial Intelligence in Education
Responding to Student Uncertainty in Spoken Tutorial Dialogue Systems
International Journal of Artificial Intelligence in Education
Emotions and Learning with AutoTutor
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Empirically building and evaluating a probabilistic model of user affect
User Modeling and User-Adapted Interaction
Responding to Learners' Cognitive-Affective States with Supportive and Shakeup Dialogues
Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Inducing positive emotional state in Intelligent Tutoring Systems
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Designing and evaluating a wizarded uncertainty-adaptive spoken dialogue tutoring system
Computer Speech and Language
New Perspectives on Affect and Learning Technologies
New Perspectives on Affect and Learning Technologies
A time for emoting: when affect-sensitivity is and isn't effective at promoting deep learning
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
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Cognitive disequilibrium and its affiliated affective state of confusion have been found to positively correlate with learning, presumably due to the effortful cognitive activities that accompany their experience. Although confusion naturally occurs in several learning contexts, we hypothesize that it can be induced and scaffolded to increase learning opportunities. We addressed the possibility of confusion induction in a study where learners engaged in trialogues on research methods concepts with animated tutor and student agents. Confusion was induced by staging disagreements and contradictions between the animated agents, and then inviting the human learners to provide their opinions. Self-reports of confusion indicated that the contradictions were successful at inducing confusion in the minds of the learners. A second, more objective, method of tracking learners' confusion consisted of analyzing learners' performance on forced-choice questions that were embedded after contradictions. This measure was also found to be revealing of learners' underlying confusion. The contradictions alone did not result in enhanced learning gains. However, when confusion had been successfully induced, learners who were presented with contradictions did show improved learning compared to a no-contradiction control. Theoretical and applied implications along with possible future directions are discussed.