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Multiple Agent Designs in Conversational Intelligent Tutoring Systems

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Abstract

This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent tutoring systems were limited to a single agent that interacted with a student in the role of a teacher or expert. Technological advances have since made possible systems in which multiple agents interact with the learner and each other to model ideal behavior, strategies, reflections, and social interactions. Though still an emerging technology, multi-agent intelligent tutoring systems afford pedagogical benefits that go beyond the capabilities of the single-agent system and have facilitated learning gains on a variety of subject matters and skills, including science, technology, engineering, mathematics, research methods, metacognition, and language comprehension. The present work describes some common multi-agent designs that may be used to achieve a variety of pedagogical goals. We provide examples of how these designs have been implemented in educational or experimental settings and anticipate future use within the field of artificial intelligence.

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Acknowledgements

The research on was supported by the National Science Foundation (SBR 9720314, REC 0106965, REC 0126265, ITR 0325428, REESE 0633918, ALT-0834847, DRK-12-0918409, 1108845), the Institute of Education Sciences (R305H050169, R305B070349, R305A080589, R305A080594, R305G020018, R305C120001), Army Research Lab (W911INF-12-2-0030), and the Office of Naval Research (N00014-00-1-0600, N00014-12-C-0643). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of NSF, IES, or DoD.

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  1. Department of Psychology and the Institute for Intelligent Systems, University of Memphis, Memphis, USA

    Anne Lippert, Keith Shubeck, Brent Morgan, Andrew Hampton & Arthur Graesser

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  1. Anne Lippert
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  2. Keith Shubeck
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  3. Brent Morgan
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  4. Andrew Hampton
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  5. Arthur Graesser
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AG, AL, BM, AH, devised the project, the main conceptual ideas and outline. KS, contributed to the future directions section of the manuscript. AL, wrote the paper with input from all authors.

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Correspondence to Anne Lippert.

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Lippert, A., Shubeck, K., Morgan, B. et al. Multiple Agent Designs in Conversational Intelligent Tutoring Systems. Tech Know Learn 25, 443–463 (2020). https://doi.org/10.1007/s10758-019-09431-8

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