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Building Intelligent Conversational Tutors and Mentors for Team Collaborative Problem Solving: Guidance from the 2015 Program for International Student Assessment

Building Intelligent Tutoring Systems for Teams

ISBN: 978-1-78754-474-1, eISBN: 978-1-78754-473-4

ISSN: 1534-0856

Publication date: 20 September 2018

Abstract

This chapter describes how conversational computer agents have been used in collaborative problem-solving environments. These agent-based systems are designed to (a) assess the students’ knowledge, skills, actions, and various other psychological states on the basis of the students’ actions and the conversational interactions, (b) generate discourse moves that are sensitive to the psychological states and the problem states, and (c) advance a solution to the problem. We describe how this was accomplished in the Programme for International Student Assessment (PISA) for Collaborative Problem Solving (CPS) in 2015. In the PISA CPS 2015 assessment, a single human test taker (15-year-old student) interacts with one, two, or three agents that stage a series of assessment episodes. This chapter proposes that this PISA framework could be extended to accommodate more open-ended natural language interaction for those languages that have developed technologies for automated computational linguistics and discourse. Two examples support this suggestion, with associated relevant empirical support. First, there is AutoTutor, an agent that collaboratively helps the student answer difficult questions and solve problems. Second, there is CPS in the context of a multi-party simulation called Land Science in which the system tracks progress and knowledge states of small groups of 3–4 students. Human mentors or computer agents prompt them to perform actions and exchange open-ended chat in a collaborative learning and problem-solving environment.

Keywords

Acknowledgements

Acknowledgments

The research was supported by the National Science Foundation (DRK-12-0918409, DRK-12 1418288), the Institute of Education Sciences (R305C120001), Army Research Lab (W911INF-12-2-0030), and the Office of Naval Research (N00014-12-C-0643; N00014-16-C-3027). 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. The Tutoring Research Group (TRG) is an interdisciplinary research team comprised of researchers from psychology, computer science, and other departments at University of Memphis (visit http://www.autotutor.org).

Citation

Graesser, A.C., Dowell, N., Hampton, A.J., Lippert, A.M., Li, H. and Shaffer, D.W. (2018), "Building Intelligent Conversational Tutors and Mentors for Team Collaborative Problem Solving: Guidance from the 2015 Program for International Student Assessment", Building Intelligent Tutoring Systems for Teams (Research on Managing Groups and Teams, Vol. 19), Emerald Publishing Limited, Bingley, pp. 173-211. https://doi.org/10.1108/S1534-085620180000019012

Publisher

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Emerald Publishing Limited

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