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Deriving Acquisition Principles from Tutoring Principles

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Intelligent Tutoring Systems (ITS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2363))

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Abstract

This paper describes our analysis of the literature on tutorial dialogues and presents a compilation of useful principles that students and teachers typically follow in making tutoring interactions successful. The compilation is done in the context of making use of those principles in building knowledge acquisition interfaces since acquisition interfaces can be seen as students acquiring knowledge from the user. We plan to use these ideas in our future work to develop more proactive and effective acquisition interfaces.

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References

  1. Aleven, V. & Koedinger, K. (2000). The need for tutorial dialog to support self-explanation. In Proceedings of the AAAI Fall Symposium on Building Dialogue Systems for Tutorial Applications.

    Google Scholar 

  2. Anderson, J. R., Conrad, F. G., & Corbett, A. T. (1989). Skill acquisition and the lisp tutor. Cognitive Science, 13:467–506.

    Article  Google Scholar 

  3. Ausubel, D. (1968). Educational psychology: A cognitive approach. New York, Holt, Rinehart and Winston.

    Google Scholar 

  4. Blythe, J.; Kim, J.; Ramachandran, S.; and Gil, Y. (2001). An integrated environment for knowledge acquisition. In Proceedings of the IUI-2001.

    Google Scholar 

  5. Brown, J. S., Burton, R., & de Kleer, J. (1982). Pedagogical natural language and knowledge engineering techniques in SOPHIE I, II, III. In Derek, S. & Brown, J. S., (Eds.), Intelligent Tutoring Systems. New York, Academic Press.

    Google Scholar 

  6. Brown, J. S. & Burton, R. R. (1978). Diagnostic models for procedural bugs in basic mathematical skills. Cognitive Science, 2:155–191.

    Article  Google Scholar 

  7. Burton, R. & Brown, J. (1979). An investigation of computer coaching for informal learning activities. International Journal of Man-Machine Studies, 11:5–24.

    Article  Google Scholar 

  8. Carbonell, J. R. (1970). AI in CAI: An artificial intelligence approach to computer-assisted instruction. IEEE Transactions on Man-Machine Systems, 11(4):190–202.

    Article  Google Scholar 

  9. Clancey, W., (Ed.) (1987). Knowledge-Based Tutoring:The GUIDON Program. MIT press.

    Google Scholar 

  10. Clark, P., Thompson, J., Barker, K., Porter, B., Chaudhri, V., Rodriguez, A., Thomere, J., Mishra, S., Gil, Y., Hayes, P., & Reichherzer, T. (2001). Knowledge entry as the graphical assembly of components. In Proceedings of K-CAP-2001.

    Google Scholar 

  11. Collins, A. & Stevens, A. L. (1982). Goals and strategies of inquiry teachers. Advances in Instructional Psychology, 2:65–119.

    Google Scholar 

  12. Core, M. G., Moore, J. D., & Zinn, C. (2000). Supporting constructive learning with a feedback planner. In Proceedings of the AAAI Fall Symposium on Building Dialogue Systems for Tutorial Applications.

    Google Scholar 

  13. Davis, R. (1979). Interactive transfer of expertise: Acquisition of new inference rules. Artificial Intelligence, 12:121–157.

    Article  Google Scholar 

  14. Eriksson, H., Shahar, Y., Tu, S. W., Puerta, A. R., & Musen, M. (1995). Task modeling with reusable problem-solving methods. Artificial Intelligence, 79:293–326.

    Article  Google Scholar 

  15. Festinger, L. (1957). A Theory of Cognitive Dissonance. Stanford University Press.

    Google Scholar 

  16. Forbus, K. & Feltovich, P., (Eds.) (2001). Smart Machines in Education. AAAI press.

    Google Scholar 

  17. Fox, B. (1993). The Human Tutorial Dialog Project. Lawrence Erlbaum.

    Google Scholar 

  18. Gaines, B. R. & Shaw, M. (1993). Knowledge acquisition tools based on personal construct psychology. The Knowledge Engineering Review, 8(1):49–85.

    Google Scholar 

  19. Gentner, D., Holyoak, K. J., & Kokinov, B. N., (Eds.) (2001). The analogical mind: Perspectives from cognitive science. MIT press.

    Google Scholar 

  20. Gil, Y. & Kim, J. (2002). Interactive knowledge acquisition tools: A tutoring perspective. http://www.isi.edu/expect/papers/Interactive-KA-Tools-gil-kim-02.pdf (internal project report).

  21. Gil, Y. & Melz, E. (1996). Explicit representations of problem-solving strategies to support knowledge acquisition. In Proceedings of the Thirteenth National Conference on Artificial Intelligence.

    Google Scholar 

  22. Ginsberg, A., Weiss, S., & Politakis, P. (1985). SEEK2: A generalized approach to automatic knowledge base refinement. In Proceedings of IJCAI-85.

    Google Scholar 

  23. Kim, J. & Gil, Y. (1999). Deriving expectations to guide knowledge base creation. In Proceedings of the Sixteenth National Conference on Artificial Intelligence, pp. 235–241.

    Google Scholar 

  24. Kim, J. & Gil, Y. (2000). Acquiring problem-solving knowledge from end users: Putting interdependency models to the test. In Proceedings of the Seventeenth National Conference on Artificial Intelligence.

    Google Scholar 

  25. Kim, J. & Gil, Y. (2002). Proactive learning for interactive knowledge capture. http://www.isi.edu/expect/papers/KA-Dialog-Kim-Gil-02.pdf (internal project report).

  26. Koedinger, K., Anderson, J., Hadley, W., & Mark, M. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8:30–43.

    Google Scholar 

  27. Kulik, J. & Kulik, C. (1988). Timing of feedback and verbal learning. Review of Educational Research, 58:79–97.

    Article  MathSciNet  Google Scholar 

  28. Lepper, M., Woolverton, M., Mumme, D., & Gurtner, J. (1993). Motivational techniques of expert human tutors: Lesson for the design of computer-based tutors. In Lajoie, S. & Derry, S., (Eds.), Computers as Cognitive Tools, pp. 75–105. Hillsdale.

    Google Scholar 

  29. Marcus, S. & McDermott, J. (1989). SALT: A knowledge acquisition language for propose-and-revise systems. Artificial Intelligence, 39(1):1–37.

    Article  MATH  Google Scholar 

  30. McDonald, J. (1981). The EXCHECK CAI system. In Suppes, P., (Ed.), University-level Computer-assisted Instruction at Stanford: 1968-1980. Stanford.

    Google Scholar 

  31. McGuinness, D. L., Fikes, R., Rice, J., & Wilde, S. (2000). An environment for merging and testing large ontologies. In Proceedings of KR-2000.

    Google Scholar 

  32. McKendree, J. (1990). Effective feedback content for tutoring complex skills. Human Computer Interactions, 5:381–413.

    Article  Google Scholar 

  33. Merrill, D. C., Reiser, B. J., Ranney, M., & Trafton, J. G. (1992). Effective tutoring techniques: A comparison of human tutors and intelligent tutoring systems. The Journal of the Learning Sciences, 2:277–305.

    Article  Google Scholar 

  34. Murray, T. (1999). Authoring intelligent tutoring systems: An analysis of the state of the art. International Journal of Artificial Intelligence in Education, 10:98–129.

    Google Scholar 

  35. Novak, J., (Ed.) (1998). Learning, Creating, and Using Knowledge: Concept Maps as Facilitative Tools in Schools and Corporations. Lawrence Erlbaum.

    Google Scholar 

  36. O’Shea, T. (1979). A self-improving Quadratic tutor. International Journal of Man-Machine Studies, 11:97–124.

    Article  Google Scholar 

  37. Rose, C. P., Jordan, P., Ringenberg, M., Siler, S., VanLehn, K., & Weinstein, A. (2001). Interactive conceptual tutoring in Atlas-Andes. In Proceedings of AI in Education.

    Google Scholar 

  38. Sleeman, D. H. (1984). Inferring student models for intelligent computer-aided instruction. In Michalski, R. S., Carbonell, J. G., & Mitchell, T. M., (Eds.), Machine Learning: An Artificial Intelligence Approach, pp. 483–510. Springer.

    Google Scholar 

  39. Stevens, A. & Collins, A. (1977). The goal structure of a Socratic tutor. In Proceedings of the National ACM Conference.

    Google Scholar 

  40. VanLehn, K., Freedman, R., Pamela, J., Murray, C., Osan, R., Ringenberg, M., Rose, C., Schulze, K., Shelby, R., Treacy, D., Weinstein, A., & Wintersgill, M. (2000). Fading and deepening: The next steps for Andes and other model-tracing tutors. In Proceedings of ITS-2000.

    Google Scholar 

  41. Wenger, E., (Ed.) (1987). Artificial Intelligence and Tutoring Systems. Morgan Kaufmann.

    Google Scholar 

  42. Woolf, B. & Allen, J. (2000). Spoken language tutorial dialogue. In Proceedings of the AAAI Fall Symposium on Building Dialogue Systems for Tutorial Applications.

    Google Scholar 

  43. Woolf, B. P. & McDonald, D. D. (1984). Building a computer tutor: Design issues. IEEE Computer, 17(9):61–73.

    Google Scholar 

  44. Zhou, Y., Freedman, R., Michael, M. G. J., Rovick, A., & Evens, M. (1999). What should the tutor do when the student cannot answer a question? In Proceedings of FLAIRS-99.

    Google Scholar 

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Kim, J., Gil, Y. (2002). Deriving Acquisition Principles from Tutoring Principles. In: Cerri, S.A., Gouardères, G., Paraguaçu, F. (eds) Intelligent Tutoring Systems. ITS 2002. Lecture Notes in Computer Science, vol 2363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47987-2_67

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  • DOI: https://doi.org/10.1007/3-540-47987-2_67

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43750-5

  • Online ISBN: 978-3-540-47987-1

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