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The role of schemata in concept acquisition and diagnosis

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Computer Assisted Learning (ICCAL 1989)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 360))

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Abstract

A module of automatic cognitive diagnosis has been constructed in the framework of a tutorial system for transmission of knowledge through language. It takes responses of students trying to characterize newly acquired concepts and evaluates them. The module contains a syntactico-semantic analyzer, a summarizer-schematizer, and an evaluator. It uses a conceptual base of knowledge organized in a hierarchy of schemata. This paper presents an important class of such schemata, concerning scientific phenomena, more specifically those in the field of animal behavior. They contain information on the entities or relations involved in the concept, their successive states, and times. They are represented in an attribute-value format. They are implemented by insertion of their components in the semantic part of the dictionary associated with the analyser. When processing a particular student response the system constructs from these schemata both a representation in working memory of the target concept and an instantiated representation of the response. Comparison of these two representations yields a diagnosis of the corresponding individual concept.

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References

  • Anderson, R. (1983) — The Architecture of Cognition, Cambridge, Mass., Harvard University Press.

    Google Scholar 

  • Bonar, J.G. and Cunningham, R. (1988) — Intelligent Tutoring with Intermediate Representations, Proc. Intelligent Tutoring Systems, Montreal.

    Google Scholar 

  • Caillot, M. (1985) — Problem representations and problem-solving procedures in electricity, in R. Duit, W. Jung and C. Von Rhoneck. Aspects of Understanding Electricity, Kiel, IPN-Arbeitsberichte, 139–151.

    Google Scholar 

  • Carbonell, J. R. (1970) — AI in CAI: An Artificial Intelligence Approach to Computer-Assisted Instruction, IEEE Trans. Man-Machine Systems, 11, 4, 190–202.

    Google Scholar 

  • Chi, M.T.H., Feltovitch, P.J. and Glaser, R.G. (1981) — Categorization and representation of physics problems by experts and novices, Cognitive Science, 5, 121–152.

    Google Scholar 

  • van Dijk, T. and Kintsch, W. (1983) — Strategies of Discourse Comprehension, New-York, Academic Press.

    Google Scholar 

  • Le Ny, J.F. (1986) — Discourse comprehension and memory for concepts. In: F. Klix and H. Hagendorf (eds). Human memory and cognitive capabilities. Amsterdam, Elsevier.

    Google Scholar 

  • Le Ny, J.F. (1987) — A quels risques peut-on inferer des representations ? In: M. Siguan (ed). Comportement, cognition, conscience. Paris, Presses Universitaires de France.

    Google Scholar 

  • Le Ny, J.F. (1989) — Science cognitive et comprehension du language, Paris, Presses Universitaires de France, in press.

    Google Scholar 

  • Le Ny J.F., Carite, L. and Poitrenaud, S. (1986) — Construction of individualized texts for the transmission of knowledge through discourse. In: I. Kurcz, G.W. Shugar and J.H. Danks (eds). Knowledge and Language, Amsterdam, Elsevier.

    Google Scholar 

  • Maida, A.S. and Shapiro, S.C. (1982) — Intensional concepts in propositional semantic networks, Cognitive Science, 6, 291–330.

    Article  Google Scholar 

  • Reiser, B.J., Anderson, J.R. and Farrell, R. G. (1985) — Dynamic Student Modelling in an Intelligent Tutor for LISP Programming, Los Angeles, Proc. IJCAI-85, 8–14.

    Google Scholar 

  • Skinner, B. F. (1938) — The Behavior of Organisms. An experimental Analysis, New York, Appleton Century Crofts.

    Google Scholar 

  • Sleeman, D. and Brown, J.S. (eds) (1982) — Intelligent Tutoring Systems, Cambridge, Mass., Academic Press.

    Google Scholar 

  • Wenger, E. (1987) — Artificial Intelligence and Tutoring Systems, Los Altos, Morgan Kaufman.

    Google Scholar 

  • Winograd, T. (1983) — Language as a cognitive process, Reading, Addison Wesley.

    Google Scholar 

  • Woods, W.A. (1972) — An Experimental Parsing System for Transition Network Grammars. In R. Rustin (ed.) Natural Language Processing, New York, Algorithmic Press, 113–154.

    Google Scholar 

  • Woolf, B. (1988) — Intelligent Tutoring Systems: A Survey, Survey Lectures from the American Association of Artificial Intelligence, Los Altos, Morgan Kaufman.

    Google Scholar 

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Hermann Maurer

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© 1989 Springer-Verlag Berlin Heidelberg

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Le Ny, JF. (1989). The role of schemata in concept acquisition and diagnosis. In: Maurer, H. (eds) Computer Assisted Learning. ICCAL 1989. Lecture Notes in Computer Science, vol 360. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-51142-3_68

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  • DOI: https://doi.org/10.1007/3-540-51142-3_68

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-51142-7

  • Online ISBN: 978-3-540-46163-0

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