Skip to main content

Mental models of recursion and their use in the SCENT programming advisor

  • Intelligent Tutoring Systems
  • Conference paper
  • First Online:
Knowledge Based Computer Systems (KBCS 1989)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 444))

Included in the following conference series:

Abstract

Mental modeling techniques are used to describe human understanding of the world, and to derive cognitive explanations of problem-solving behaviour. This paper identifies mental models of recursion through an investigation conducted among novice programmers. The necessity of using these mental models in diagnosis, pedagogy, and student modeling in an intelligent tutoring system is illustrated with the aid of a case study. The evolutionary and possible revolutionary development of mental models, coexistence of multiple models, and representation of these models are also discussed.

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

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Anderson, JR and Reiser, B. The LISP Tutor, Byte, pp. 159–175, April, 1986.

    Google Scholar 

  2. Anzai, Y and Uesato, Y. Learning Recursive Procedures by Middle School Children. Proceedings of the Fourth Annual Conference of the Cognitive Science Society, pp. 100–102, Ann Arbor, Michigan, USA, 1982.

    Google Scholar 

  3. Bhuiyan, SH. Mental Models of Recursion in Computer Programming. Proceedings of the First Annual Graduate Symposium on Computational Science, pp. 286–313, Dept of Computational Science, University of Saskatchewan, Canada, 1989.

    Google Scholar 

  4. Chi MTH, Feltovich PJ and Glaser R. Categorization and Representation of Physics Problems by Experts and Novices. Cognitive Science, 5, pp. 121–152, 1982.

    Google Scholar 

  5. Conant RC and Ashby S. Every Good Regulator of a System Must be a Good Model of the System. International Journal of System Science, 1, pp. 89–97, 1970.

    Google Scholar 

  6. Escott J. Problem Solving by Analogy in Novice Programming. ARIES LAB Research Report 88-3. Dept of Computational Science, University of Saskatchewan, Canada, 1988.

    Google Scholar 

  7. Gentner D and Stevens A. (Eds). Mental Models. Hillside, NJ: Lawrence Erlbaum, 1983.

    Google Scholar 

  8. Greer JE. Empirical Comparison of Techniques for Teching Recursion in Introductory Computer Science. Ph.D. Thesis. The University of Texas at Austin, 1987.

    Google Scholar 

  9. Greer JE and McCalla GI. A Computational Framework for Granularity and its Application to Educational Diagnosis. Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 477–482, Detroit, August, 1989.

    Google Scholar 

  10. Kahney H. An In-depth Study of the Cognitive Behaviour of Novice Programmers. Tech. Report No. 5. Milton-Keynes, England: The Open University, 1982.

    Google Scholar 

  11. Kessler CM and Anderson JR. Learning Flow of Control: Iterative and Recursive Procedures. Human-Computer Interaction, Volume 2, Hillside, NJ: Lawrence Erlbaum, pp. 135–166, 1986.

    Google Scholar 

  12. McCalla GI, Greer JE and the SCENT Research Team. Intelligent Advising in Problem Solving Domains: The SCENT-3 Architecture. Proceedings of Intelligent Tutoring Systems, Montreal, Canada, pp. 124–131, 1988.

    Google Scholar 

  13. Pirolli PA. A Cognitive Model of Computer Tutor for Programming Recursion. Human-Computer Interaction, Volume 2, Hillside, NJ: Lawrence Erlbaum, pp. 329–355, 1988.

    Google Scholar 

  14. Rouse WB and Morris NM. On Looking into the Black Box: Prospects and Limits in the Search of Mental Models. Technical Report, 85-2. Center for Man-Machine Systems Research, GIT, Atlanta, USA.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

S. Ramani R. Chandrasekar K. S. R. Anjaneyulu

Rights and permissions

Reprints and permissions

Copyright information

© 1990 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bhuiyan, S., Greer, J., McCalla, G. (1990). Mental models of recursion and their use in the SCENT programming advisor. In: Ramani, S., Chandrasekar, R., Anjaneyulu, K.S.R. (eds) Knowledge Based Computer Systems. KBCS 1989. Lecture Notes in Computer Science, vol 444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0018374

Download citation

  • DOI: https://doi.org/10.1007/BFb0018374

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-52850-0

  • Online ISBN: 978-3-540-47168-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics