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Tools for building knowledge-based tutors

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Abstract

DESCRIBED IS THE PROCESS OF ENCODING TUTORING KNOWLEDGE in a knowledge-based tutor, and the tools that facilitate identifying the tutoring knowledge and the process of representing it.Knowledge representation is explained in terms of modelling domain knowledge, human thinking, learning processes, and tutoring strategies. A uniform language is proposed for storing tutoring primitives, including lessons, topics, and presentations.Knowledge acquisition is described as a methodology for identifying and encoding the expertise used by teachers to reason about tutoring.Control knowledge is explained in terms of the machine’s ability to select a topic or response for an individual student and then customize its discourse and dynamically modify its examples, questions, or descriptions for that student.

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References

  • Atkins, T. (1982).The second law. San Francisco: Freedman.

    Google Scholar 

  • Brown, D., Clement, J., & Murray, T. (1986). Tutoring specifications for a computer program which uses analogies to teach mechanics.Cognitive Processes Research Group Working Paper, Department of Physics, University of Massachusetts, Amherst, MA.

    Google Scholar 

  • Duckworth, E., Kelley, J., & Wilson S. (November 1987). AI goes to school.Academic Computing, pp. 6–10, 38–43, 62–63.

  • Gonzalez, A., & Zimbardo, P. (1985, March). Time in perspective.Psychology Today. 21–26.

  • McCalla, G., Greer, J., & the Scent Team (1988). Intelligent advising in problem solving domains: the scent-3 architecture.Proceedings of the International Conference on Intelligent Tutoring Systems (pp. 124–133). University of Montreal, Canada.

    Google Scholar 

  • MacMillian, S., Emme D., & Bekowitz, M. (1988). Instructional planners: lessons learned: In J. Psotka, L.D. Massey & S. Mutter (Eds.),Intelligent tutoring systems: lessons learned, pp. 229–256. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Murray, W. (1988). Control for intelligent tutoring systems: a comparison of blackboard architectures and discourse management networks.FMC Technical Reports #R-6267.

  • Murray, T., Schultz, K., Brown, D., & Clement, J. (1990). An analogy-based computer tutor for remediating physics misconception. Journal of Interactive Learning Environments,1(2), 79–101.

    Article  Google Scholar 

  • Reichman, R. (1985).Making computers talk like you and me. Cambridge, MA: MIT Press.

    Google Scholar 

  • Servan-Schreiber, D. (1983). Artificial intelligence in psychiatry.Journal of Nervous and Mental Disease, 174, 191–202.

    Google Scholar 

  • Servan-Schreiber, D. (1987). From intelligent tutoring to computerized psychotherapy. InProceedings of the Sixth National Conference of Artifical Intelligence (AAAI-87). pp. 66–71. Los Altos, CA: Morgan Kaufmann.

    Google Scholar 

  • Slovin, T., & Woolf, B.P. (1988). A consultant tutor for personal development.Proceedings of the International Conference on Intelligent Tutoring Systems (pp. 162–169). University of Montreal.

  • Suthers, D., & Rissland, E. (1988). Ex gen: a constraint satisfying example generator.Computer and Information Science Department Technical Report #88-71, University of Massachusetts, Amherst, MA.

    Google Scholar 

  • Wenger, E. (1988).Artificial intelligence and tutoring systems. Los Altos, CA: Morgan Kaufmann Publishers.

    Google Scholar 

  • Woods, W. (1970). Transition network grammars for natural language analysis.Communications of the ACM, 13(10), 591–606.

    Article  Google Scholar 

  • Woolf, B., & Cunningham, P. (1987). Multiple knowledge sources in intelligent tutoring systems.IEEE Expert 2, Summer, pp. 41–54.

    Article  Google Scholar 

  • Woolf, B., Suthers, D., & Murray, T. Discourse control for tutoring: case studies in example generation. To be printed as a Computer and Information Science Department Technical Report, University of Massachusetts, Amherst, MA.

  • Woolf, B., & Murray, T. (1987). A framework for representing tutorial discourse.International joint conference in artificial intelligence (IJCAI-87). (pp. 189–192). Los Altos, CA: Morgan Kaufmann.

    Google Scholar 

  • Yankelovich, N., Meyrowitz, N., & van Dam, A. (1987). Reading and writing the electronic book.IEEE Computer, 20(9), 15–30.

    Google Scholar 

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Authors and Affiliations

  1. University of Massachusetts, USA

    Beverly Woolf

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  1. Beverly Woolf
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Woolf, B. Tools for building knowledge-based tutors. J. Comput. High. Educ. 2, 103–129 (1990). https://doi.org/10.1007/BF02941584

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