• DocumentCode
    3740410
  • Title

    Modeling Curiosity in Virtual Companions to Improve Human Learners´ Learning Experience

  • Author

    Qiong Wu;Chunyan Miao;Cyril Leung

  • Author_Institution
    Joint NTU-UBC Res. Centre of Excellence in Active Living for the Elderly, Nanyang Technol. Univ., Singapore, Singapore
  • Volume
    2
  • fYear
    2015
  • Firstpage
    59
  • Lastpage
    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.
  • Keywords
    "Appraisal","Computational modeling","Planning","Uncertainty","Virtual environments","Psychology","Knowledge representation"
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2015.242
  • Filename
    7397337