Research-Based Design of Pedagogical Agent Roles: a Review, Progress, and Recommendations

教育技术 计算机科学 工程伦理学 数学教育 管理科学 知识管理 工程管理 心理学 工程类
作者
Amy L. Baylor,Yanghee Kim
出处
期刊:International Journal of Artificial Intelligence in Education [Springer Science+Business Media]
卷期号:26 (1): 160-169 被引量:184
标识
DOI:10.1007/s40593-015-0055-y
摘要

This paper describes the design and empirical validation of three distinct pedagogical agent roles (Expert, Motivator, and Mentor) for college students within the MIMIC (Multiple Intelligent Mentors Instructing Collaboratively) agent-based research environment. The pedagogical agent roles were operationalized by image, animation, affect, voice and script, and were developed in Poser 4 and implemented via Microsoft Agent. Two controlled experiments validated the instantiation of the three roles according to learner perception (N=78) and actual impact on motivation and learning (N=71). The results confirmed that the agent roles were not only perceived by the students to reflect their intended purposes but also led to significant changes in learning and motivation, as designed. Specifically, the Expert agent led to increased information acquisition, the Motivator led to increased self-efficacy, and the Mentor led to overall improved learning and motivation. The implications for intelligent tutoring and multi-agent system design and development is discussed.

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