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2015 IEEE / WIC / ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (2015)
Singapore, Singapore
Dec. 6, 2015 to Dec. 9, 2015
ISBN: 978-1-4673-9617-2
pp: 59-66
ABSTRACT
A key design aspect for virtual learning companions is their believability. A lot of attention has been paid to emotion modeling which is at the core of believability. However, most of the existing emotion models neglect the epistemology-based emotions, which are knowledge-related emotions that affect the human learning process. Studies have shown that curiosity is an important epistemology-based emotion that positively influences social learning. Hence, modeling curiosity in learning companions may improve human learners' learning experience in a virtual environment. However, existing curiosity models assume simplified cognitive processes and fail to capture multiple sources of curiosity stimuli. In this paper, we propose a novel model of curiosity for learning companions to capture salient curiosity stimuli through a psychologically inspired approach. Our model is built based on Berlyne's theory and considers three most salient appraisal variables in a virtual learning environment, including novelty, surprise, and uncertainty. The model is built on planbased knowledge representations augmented with planning. Two internal processes are modeled for learning companions to demonstrate curiosity: curiosity appraisal and learning. The proposed model of curiosity is implemented in a learning companion and evaluated through user studies. The evaluation results show that the learning companion's curiosity significantly improves human learners' learning experience from multiple aspects.
INDEX TERMS
Appraisal, Computational modeling, Planning, Uncertainty, Virtual environments, Psychology, Knowledge representation
CITATION

Q. Wu, C. Miao and C. Leung, "Modeling Curiosity in Virtual Companions to Improve Human Learners' Learning Experience," 2015 IEEE / WIC / ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Singapore, Singapore, 2015, pp. 59-66.
doi:10.1109/WI-IAT.2015.242
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