The persona effect: affective impact of animated pedagogical agents
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Affective computing
What Video Games Have to Teach Us About Learning and Literacy
What Video Games Have to Teach Us About Learning and Literacy
Emotion Recognition Based on Joint Visual and Audio Cues
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Diagnosing and acting on student affect: the tutor's perspective
User Modeling and User-Adapted Interaction
Cross-Cultural Evaluation of Politeness in Tactics for Pedagogical Agents
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
The role of learning goals in the design of ILEs: Some issues to consider
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Cohesion Relationships in Tutorial Dialogue as Predictors of Affective States
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Unobtrusive multimodal emotion detection in adaptive interfaces: speech and facial expressions
FAC'07 Proceedings of the 3rd international conference on Foundations of augmented cognition
Enhancing learning with off-task social dialogues
EC-TEL'10 Proceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice
Towards Systems That Care: A Conceptual Framework based on Motivation, Metacognition and Affect
International Journal of 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
On modeling the affective effect on learning
MIWAI'11 Proceedings of the 5th international conference on Multi-Disciplinary Trends in Artificial Intelligence
| Hi-index | 0.00 |
This paper reviews and integrates research that would be necessary to develop an AIED system able to detect and then appropriately react to an affective state of a learner. It addresses the nature of affect, methods to automatically detect affect, as well as the interplay between affect and learning-related cognition, and affective strategies that promote quality learning.