Abstract
Dynamic communication between Teachable Agents (TA) and students is crucial for educational effectiveness of the TA, as dynamic interaction is the vital part throughout the teaching and learning processes. Existing TA design mainly focuses on the functions and features to ensure the TA to be taught by students rather than bi-directional interaction. However, according to reciprocity theory in social psychology, if the TA can offer friendly actions, students in response will be much more cooperative and motivated. In order to improve quality of communication and seize the interest of students, we propose a need modeling approach to enable TAs to have “intrinsic motivations”. In this way, the TA can proactively carry out dynamic communication with students so that the TA can adapt to students’ changing behaviors and sustain a good human-agent relationship. Our field study showed that students were highly attracted by the TA with dynamic needs. They statistically completed more tasks. Also, better results were obtained on students’ learning efficiency and attitude towards TA’s informational usefulness and affective interactions.
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Borjigin, A., Miao, C., Lim, S.F., Li, S., Shen, Z. (2015). Teachable Agents with Intrinsic Motivation. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_4
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DOI: https://doi.org/10.1007/978-3-319-19773-9_4
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