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Probabilistic assessment of knowledge

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Book cover Knowledge Structures

Abstract

An easy and common way of assessing a student’s knowledge consists of a written examination. A list of questions is presented, the student’s answers are collected, and finally the examiner returns an appreciation, which usually boils down to a single number or percentage. Table 1.1 presents an excerpt of such a test in elementary arithmetics and will be used for exemplary purpose. We first argue that the information provided by the testing procedure is poorly reflected by a single number. Knowing that a student provided correct answers only to questions, say, α, c, and e, entails more than a numerical appreciation (60% correct) of his or her work. It shows mastery in performing multiplications, and deficiency in division operations. Weaknesses and strengthes of the student’s preparation have thus been revealed. Hence advices for further study can be inferred.

Our work in this area is supported by NSF grant IRI 8919068 to Jean-Claude Falmagne at the University of California, Irvine. We thank the editor and three anonymous referees for their careful reading of a preliminary version of the manuscript, and for their useful remarks.

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Bibliography

References on knowledge structures and assessment

  • Degreef, E., Doignon, J.-P., Ducamp, A., Sr Falmagne, J.-C. (1986). Languages for the assessment of knowledge. Journal of Mathematical Psychology, 30, 243–256.

    Google Scholar 

  • Doignon, J.-P., Sc Falmagne, J.-C. (1985). Spaces for the assessment of knowledge. International Journal of Man-Machine Studies, 23, 175–196.

    Article  Google Scholar 

  • Dowling, C. E. (1991a). Constructing knowledge spaces from judgements with differing degrees of certainty. In J.-P. Doignon u. J.-C. Falmagne (Eds.), Mathematical psychology: Current Developments (pp. 221–231 ). New York: Springer.

    Google Scholar 

  • Dowling, C. E. (1991b). Constructing Knowledge Structures from the Judgements of Experts. Habilitationsschrift, Technische Universität Carolo-Wilhelmina, Braunschweig, Germany.

    Google Scholar 

  • Falmagne, J.-C. (1989a). A latent trait theory via stochastic learning theory for a knowledge space. Psychometrika, 53, 283–303.

    Article  Google Scholar 

  • Falmagne, J.-C. (in press,a). Finite Markov learning models for knowledge structures. In G. H. Fischer u. D. Laming (Eds.), Contributions to Mathematical Psychology, Psychometrics, and Methodology. New York: Springer. To appear.

    Google Scholar 

  • Falmagne, J.-C. (in press,b). Stochastic learning paths in a knowledge structure. Journal of Mathematical Psychology.

    Google Scholar 

  • Falmagne, J.-C., u. Doignon, J.-P. (1988a). A class of stochastic procedures for the assessment of knowledge. British Journal of Mathematical and Statistical Psychology, 41, 1–23.

    Article  Google Scholar 

  • Falmagne, J.-C., u. Doignon, J.-P. (1988b). A Markovian procedure for assessing the state of a system. Journal of Mathematical Psychology, 32, 232–258.

    Article  Google Scholar 

  • Falmagne, J.-C., Koppen, M., Villano, M., Doignon, J.-P., u. Johannesen, L. (1990). Introduction to knowledge spaces: How to build, test and search them. Psycho-logical Review, 97, 201–224.

    Google Scholar 

  • Kambouri, M. (1991). Knowledge assessment: A comparison between human experts and computerized procedure. Doctoral dissertation, New York University.

    Google Scholar 

  • Kambouri, M., Koppen, M., Villano, M., u. Falmagne, J.-C. (in press). Knowledge assessment: tapping human expertise by the QUERY routine. International Journal of Man-Machine Studies.

    Google Scholar 

  • Koppen, M. (1991). On alternative representations for knowledge spaces Manuscript submitted for publication.

    Google Scholar 

  • Koppen, M. (1993). Extracting human expertise for constructing knowledge spaces: An algorithm. Journal of Mathematical Psychology, 37, 1–20.

    Article  Google Scholar 

  • Koppen, M., u. Doignon, J.-P. (1990). How to build a knowledge space by querying an expert. Journal of Mathematical Psychology, 34, 311–331.

    Google Scholar 

  • Muller, C. E. (1989). A procedure for facilitating an expert’s judgments on a set of rules. In E. E. Roskam (Ed.), Mathematical psychology in progress (pp. 157–170 ). Berlin: Springer.

    Chapter  Google Scholar 

  • Theuns, P. (1992). Dichotomization methods in Boolean analysis of co-occurrence data. Doctoral dissertation, Vrije Universiteit Brussel, Brussels, Belgium.

    Google Scholar 

  • Villano, M. (1991). Computerized knowledge assessment: Building the knowledge structure and calibrating the assessment routine (Doctoral dissertation, New York University, New York). Dissertation Abstracts International, 552, 12B.

    Google Scholar 

  • Villano, M., Falmagne, J.-C., Johannesen, L., u. Doignon, J.-P. (1987). Stochastic procedures for assessing an individual’s state of knowledge. Proceedings of the International Conference on Computer-assisted Learning in Post-Secondary Education, Calgary 1987 (pp. 369–371 ). Calgary: University of Calgary Press.

    Google Scholar 

Other references for combinatorial results

  • Birkhoff, G. (1937). Rings of sets. Duke Mathematical Journal, 3, 443–454.

    Article  Google Scholar 

  • Hyafil, L., u. Rivest, R. L. (1976). Constructing optimal decision trees is NP-complete. Information Processing Letters, 5, 15–17.

    Article  Google Scholar 

Manuals on Markov chains

  • Chung, K. L. (1974). Elementary probability theory with stochastic processes. New York: Springer.

    Book  Google Scholar 

  • Feller, W. (1970). An introduction to probability theory and its applications. New York: Wiley.

    Google Scholar 

  • Kemeny, J. G., u. Snell, J. L. (1965). Finite Markov chains. Princeton: Van Norstrand.

    Google Scholar 

Manuals on artificial intelligence

  • Barr, A., Feigenbaum, E. A. (Eds.). (1981). The handbook of artificial intelligence. London: Pitman.

    Google Scholar 

  • Rich, E. (1983). Artificial intelligence. Singapore: McGraw-Hill.

    Google Scholar 

Further reading

  • Albert, D., Schrepp, M., u. Held, Th. (in press). Construction of knowledge spaces for problem solving in chess. In G.H. Fischer u. D. Laming (Eds.), Contributions to Mathematical Psychology, Psychometrics, and Methodology. New York. Springer. To appear.

    Google Scholar 

  • Bloom, C., Villano, M., u. VanLehn, K. (1992). Application of artificial intelligence technologies to training systems: Computer-based diagnostic testing systems (Contract No. F41624–91—C-5002). Brooks AFB, TX: Technical Training Research Division, Human Resources Directorate.

    Google Scholar 

  • Doignon, J.-P. (in press). Knowledge spaces and skill assignments. In G. H. Fischer u. D. Laming (Eds.), Contributions to Mathematical Psychology, Psychometrics, and Methodology. New York: Springer. To appear.

    Google Scholar 

  • Doignon, J.-P., u. Falmagne, J.-C. (1987). Knowledge assessment: A set theoretical framework. In B. Ganter, R. Wille, u. K.E. Wolfe (Eds.), Beiträge zur Begriffsanalyse, Vorträge der Arbeitstagung Begriffsanalyse, Darmstadt 1986 (pp. 129–140). Mannheim: B. I. Wissenschaftsverlag.

    Google Scholar 

  • Doignon, J.-P., u. Falmagne, J.-C. (1988). Parametrization of knowledge structures. Discrete Applied Mathematics, 21, 87–100.

    Article  Google Scholar 

  • Dowling, C. E. (1993a). On the irredundant construction of knowledge spaces. Journal of Mathematical Psychology, 37, 21–48.

    Article  Google Scholar 

  • Dowling, C. E. (1993b). Applying the basis of a knowledge space for controlling the questioning of an expert. Journal of Mathematical Psychology, 37, 49–62.

    Article  Google Scholar 

  • Dowling, C. E. (in press). Integrating Different Knowledge Spaces. In G. H. Fischer u. D. Laming (Eds.), Contributions to Mathematical Psychology, Psychometrics, and Methodology. New York. Springer. To appear.

    Google Scholar 

  • Dowling, C. E., u. Malinowski, U. (in preparation). Determining knowledge structures for a CAD tutorial.

    Google Scholar 

  • Falmagne, J.-C. (1989b). Probabilistic knowledge spaces: A review. In F. S. Roberts (Ed.), Applications of Combinatorics and Graph Theory to the Biological and Social Sciences (IMA Vol. 17, pp. 283–303 ). New York: Springer.

    Google Scholar 

  • Falmagne, J.-C. u. Doignon, J.-P.(1993). A stochastic theory for system failure assessment. In B. Bouchon-Meunier, L. Valverde u. R. R. Yager (Eds.), Uncertainty in Intelligent Systems. Amsterdam: North-Holland.

    Google Scholar 

  • Koppen, M. (1989). Ordinal Data Analysis: Biorder Representation and Knowledge Spaces. Doctoral Dissertation, Katholieke Universiteit to Nijmegen, Nijmegen, The Netherlands.

    Google Scholar 

  • Koppen, M. (in press). The construction of knowledge spaces by querying experts. In G. H. Fischer u. D. Laming (Eds.), Contributions to Mathematical Psychology, Psychometrics, and Methodology. New York: Springer. To appear.

    Google Scholar 

  • Lukas, J., u. Albert, D. (1993). Knowledge assessment based on skill assignment and psychological task analysis. In G. Strube u. K. F. Wender (Eds.), The Cognitive Psychology of Knowledge (pp. 139–159). Amsterdam: Elsevier.

    Google Scholar 

  • Unnewehr, J. (1992). Benutzerhandbuch Prozeduren zur Wissendiagnose. Bericht aus dem Psychologischen Institut der Universität Heidelberg (pp. 1–39+5).

    Google Scholar 

  • Unnewehr, J. (1993). Knowledge Assessment Procedures 2.0. Arbeitsbericht aus dem Projekt “Wissensstruktur” (pp. 1–7+2).

    Google Scholar 

  • Villano, M. (1992). Probabilistic student models: Bayesian belief networks and knowledge space theory. Proceedings of the Second International Conference on Intelligent Tutoring Systems ( 491–498 ). New York, Springer, Lecture Notes in Computer Science.

    Google Scholar 

  • Villano, M., u. Bloom, C. (1992). Probabilistic Student Modelilng with Knowledge Space Theory. (Contract No. F33615–01-C-0002). Brooks AFB, TX: Technical Training Research Division Human Resources Directorate.

    Google Scholar 

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© 1994 Springer-Verlag Berlin Heidelberg

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Doignon, JP. (1994). Probabilistic assessment of knowledge. In: Albert, D. (eds) Knowledge Structures. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-52064-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-52064-8_1

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