Skip to main content
SpringerLink
Log in

Fading and Deepening: The Next Steps for Andes and Other Model-Tracing Tutors

  • Conference paper
  • First Online:
Book cover Intelligent Tutoring Systems (ITS 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1839))

Included in the following conference series:

Abstract

Model tracing tutors have been quite successful in teaching cognitive skills; however, they still are not as competent as expert human tutors. We propose two ways to improve model tracing tutors and in particular the Andes physics tutor. First, tutors should fade their scaffolding. Although most model tracing tutors have scaffolding that needs to be gradually removed (faded), Andes’ scaffolding is already “faded,” and that causes student modeling difficulties that adversely impact its tutoring. A proposed solution to this problem is presented. Second, tutors should integrate the knowledge they currently teach with other important knowledge in the task domain in order to promote deeper learning. Several types of deep learning are discussed, and it is argued that natural language processing is necessary for encouraging such learning. A new project, Atlas, is developing natural language based enhancements to model tracing tutors that are intended to encourage deeper learning.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aleven, V., Koedinger, K. R., & Cross, K. (1999). Tutoring answer-explanation fosters learning with understanding, Artificial Intelligence in Education (pp. 199–206). Amsterdam: IOS Press.

    Google Scholar 

  2. Aleven, V., Koedinger, K. R., Sinclair, H. C., & Snyder, J. (1998). Combating shallow learning in a tutor for geometry problem solving. In B.P. Goettle, H. M. Halff, C. L. Redfield, & V. J. Shute (Eds.), Intelligent Tutoring Systems, Proceedings of the Fourth International Conference (pp. 364–373). Berlin: Spring-Verlag.

    Google Scholar 

  3. Anderson, J. R., Boyle, C. F., & Reiser, B. J. (1985). Intelligent tutoring systems. Science, 228, 456–462.

    Google Scholar 

  4. Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive Tutors: Lessons Learned. The Journal of the Learning Sciences, 4(2), 167–207.

    Article  Google Scholar 

  5. Chi, M. T. H., Feltovich, P., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.

    Article  Google Scholar 

  6. Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing and mathematics. In L.B. Resnick (Ed.), Knowing, learning and instruction: Essays in honor of Robert Glaser (pp. 543–494). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  7. Collins, A., & Stevens, A. (1982). Goals and methods for inquiry teachers. In R. Glaser (Ed.), Advances in Instructional Psychology, Vol. 2. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  8. DiEugenio, B., Jordan, P. W., Thomason, R. H., & Moore, J. D. (in press). The agreement process: An empirical investigation of human-human computer-mediated dialogues. International Journal of Human-Computer Studies.

    Google Scholar 

  9. Freedman, R., & Evens, M. W. (1996). Generating and revising hierarchical multi-turn text plans in an ITS. In C. Frasson, G. Gauthier, & A. Lesgold (Eds.), Intelligent Tutoring Systems: Proceedings of the 1996 Conference (pp. 632–640). Berlin: Springer.

    Google Scholar 

  10. Freedman, R., Rose, C. P., Ringenberg, M. A., & VanLehn, K. (2000). ITS Tools for natural language dialogue: A domain-independent parser and planner. In C. Frasson (Ed.), Proceedings of ITS 2000.. Berlin: Springer-Verlag.

    Google Scholar 

  11. Gertner, A., Conati, C., & VanLehn, K. (1998). Procedural help in Andes: Generating hints using a Bayesian network student model., Proceedings of the 15th national Conference on Artificial Intelligence.

    Google Scholar 

  12. Gertner, A. S. (1998). Providing feedback to equation entries in an intelligent tutoring system for Physics. In B. P. Goettl, H. M. Halff, C. L. Redfield, & V. J. Shute (Eds.), Intelligent Tutoring Systems: 4th International Conference (pp. 254–263). New York: Springer.

    Google Scholar 

  13. Gertner, A. S., & VanLehn, K. (2000). Andes: A coached problem solving environment for physics. In C. Frasson (Ed.), Proceedings of ITS 2000. New York: Springer.

    Google Scholar 

  14. Graesser, A. C., Person, N., & Magliano, J. (1995). Collaborative dialog patterns in naturalistic one-on-one tutoring. Applied Cognitive Psychology, 9, 359–387.

    Article  Google Scholar 

  15. Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. The Physics Teacher, 30, 141–158.

    Article  Google Scholar 

  16. Koedinger, K., & Anderson, J. R. (1993). Reifying implicit planning in geometry: Guidelines for model-based intelligent tutoring system design. In S. P. L. a. S. J. Derry (Ed.), Computers as cognitive tools. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  17. Koedinger, K. R., Anderson, J. R., Hadley, W. H., & Mark, M. A. (1995). Intelligent tutoring goes to school in the big city. In J. Greer (Ed.), Proceedings of the 7th World Conference on Artificial Intelligence and Education (pp. 421–428). Charlottesville, NC: AACE.

    Google Scholar 

  18. Lewis, C. (1981). Skill in algebra. In J. R. Anderson (Ed.), Cognitive skills and their acquisition (pp. 85–110). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  19. Mark, M. A., & Greer, J. E. (1995). The VCR tutor: Effective instruction for device operation. The Journal of the Learning Sciences, 4(2), 209–246.

    Article  Google Scholar 

  20. McArthur, D., Stasz, C., & Zmuidzinas, M. (1990). Tutoring techniques in algebra. Cognition and Instruction, 7(3), 197–244.

    Article  Google Scholar 

  21. McKendree, J., Radlinski, B., & Atwood, M. E. (1992). The Grace Tutor: A qualified success. In C. Frasson, G. Gautheir, & G. I. McCalla (Eds.), Intelligent Tutoring Systems: Second International Conference (pp. 677–684). Berlin: Springer-Verlag.

    Google Scholar 

  22. Merrill, D. C., & Reiser, B. J. (1994). Scaffolding effective problem solving strategies in interactive learning environments. In A. R. a. K. Eiselt (Ed.), Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society (pp. 629–634). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  23. Reif, F., & Scott, L. A. (1999). Teaching scientific thinking skills: Students and computers coaching each other. American Journal of Physics, 67(9), 819–831.

    Article  Google Scholar 

  24. Reiser, B. J., Beekelaar, R., Tyle, A., & Merrill, D. C. (1991). Gil: Scaffolding learning to program with reasoning-congruent representations. In L. Birnbaum (Ed.), The International Conference of the Learning Sciences: Proceedings of the 1991 Conference (pp. 382–388). Charlottesville, NC: Association for the Advancement of Computers in Education.

    Google Scholar 

  25. Reiser, B. J., Copen, W. A., Ranney, M., Hamid, A., & Kimberg, D. Y. (in press). Cognitive and motivational consequences of tutoring and discovery learning. Cognition and Instruction.

    Google Scholar 

  26. Reiser, B. J., Kimberg, D. Y., Lovett, M. C., & Ranney, M. (1992). Knowledge representation and explanation in GIL, an intelligent tutor for programming. In J. H. a. C. Larkin, R.W. (Ed.), Computer Assisted Instruction and Intelligent Tutoring Systems: Shared Goals and Complementary Approaches (pp. 111–150). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  27. Rose, C. P., & Lavie, A. (in press). Balancing robustness and efficiency in unificationaugmented context-free parsers for large practical applications. In J. C. Junqua & G. V. Noord (Eds.), Robustness in Language and Speech Technology: Kluwer Academic press.

    Google Scholar 

  28. Shelby, R. N., Schulze, K. G., Treacy, D. J., Wintersgill, M. C., Gertner, A. G., & Vanlehn, K. (in prep.). The Andes Intelligent Tutor: an Evaluation.

    Google Scholar 

  29. Shute, V. J. (1993). A macroadaptive approach to tutoring. Journal of Artificial Intelligence in Education, 4(1), 61–93.

    Google Scholar 

  30. Singley, M. K. (1990). The reification of goal structures in a calculus tutor: Effects on problem solving performance. Interactive Learning Environments, 1, 102–123.

    Article  Google Scholar 

  31. VanLehn, K. (1988). Student modeling. In M. Polson & J. Richardson (Eds.), Foundations of Intelligent Tutoring Systems (pp. 55–78). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  32. VanLehn, K. (1996). Conceptual and meta learning during coached problem solving. In C. Frasson, G. Gauthier, & A. Lesgold (Eds.), ITS96: Proceeding of the Third International conference on Intelligent Tutoring Systems.. New York: Springer-Verlag.

    Google Scholar 

  33. VanLehn, K., Siler, S., Murray, C., & Baggett, W. B. (1998). What makes a tutorial event effective? In M. A. Gernsbacher & S. J. Derry (Eds.), Proceedings of the Twentieth Annual Conference of the Cognitive Science Society (pp. 1084–1089). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  34. VanLehn, K., Siler, S., Murray, C., Yamauchi, T., & Baggett, W. B. (in press). Human tutoring: Why do only some events cause learning? Cognition and Instruction.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, 15260

    Kurt VanLehn, Reva Freedman, Pamela Jordan, Charles Murray, Remus Osan, Michael Ringenberg, Carolyn Rosé & Anders Weinstein

  2. Department of Physics, United States Naval Academy, USA

    Robert Shelby, Donald Treacy & Mary Wintersgill

  3. Computer Science Department, United States Naval Academy, USA

    Kay Schulze

Authors
  1. Kurt VanLehn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Reva Freedman
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pamela Jordan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Charles Murray
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Remus Osan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michael Ringenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Carolyn Rosé
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Kay Schulze
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Robert Shelby
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Donald Treacy
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Anders Weinstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Mary Wintersgill
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Département d’informatique, Université du Québec á Montréal, C.P. 8888, succ. Centre-Ville, Montréal, QC, Canada, H3C 3P8

    Gilles Gauthier

  2. Département d’informatique et de recherche opérationnelle, Université de Montréal, C.P. 6128, succ. Centre-Ville, Montréal, QC, Canada, H3C 3J7

    Claude Frasson

  3. Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, 15260, USA

    Kurt VanLehn

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

VanLehn, K. et al. (2000). Fading and Deepening: The Next Steps for Andes and Other Model-Tracing Tutors. In: Gauthier, G., Frasson, C., VanLehn, K. (eds) Intelligent Tutoring Systems. ITS 2000. Lecture Notes in Computer Science, vol 1839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45108-0_51

Download citation

  • DOI: https://doi.org/10.1007/3-540-45108-0_51

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67655-3

  • Online ISBN: 978-3-540-45108-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation