Abstract
In this paper we discuss the principles of the design of a student model module within an educational teaching program in the domain of vertical projectile motion. Taking into account knowledge in the students as well as their individual learning skills the model allows steering of the educational process through the use of fuzzy logic and quantitative measurements. The teacher can still adapt the teaching strategy to specific needs of the student. The model has a decision component which chooses the teaching strategy on the basis of recorded history. A prototype program of the ‘Fuzzy student model’ is described.
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Dillenburg, P. (1988) A progmatic approach to student modelling: principles and architecture of PROTO-TEG. Intelligent Tutoring-System. Summer University Le Mans 88.
Self, J. (1988) Bypassing the intractable problem of student modelling. Intelligent Tutoring Systems. Montreal, Quebec, Canada: Université de Montreal.
Martin, J. and Vanlehn, K. (1993) OLAE: Progress toward a multi-activity, Bayesian student modeler. Proceedings of AI-ED 93. Edinburgh, Scotland.
Panagiotou, M., Grigoriadou, M., Metaxaki, Chr. and Philokiprou, G. (1989) Modelling the student in a tutoring system. Proceedings of the 6th Int. Conf. on Techology and Education. Orlando. Vol. 2.
Nawrocki (1987) Maintenance in Training. Kearsley, G. (ed.) Artificial Intelligence and Instuction: Application and Methods. Addison-Wesley.
Mandl, H. and Lesgold, A. (1988) Learning Issues for Intelligent Tutoring Systems. New York Springer.
Berteis, K. (1994) A Dynamic View on Cognitive Student Modeling in Computer Programming. Journal of Artificial Intelligence in Education 5(1).
Zadeh L. A. (1988) Fuzzy Logic. IEEE Computer, April 1988.
Novak, V. (1988) Fuzzy Sets and their Applications. Adam Higler.
Emberson, S. (1990) Diagnostic Testing by Measuring Learning Processes: Psychometric Considerations for Dynamic Testing. In Frederiksen, N., Glaser, R., Lesgold, A. and Saffo M. G. (eds.) Diagnostic monitoring of skill and knowledge acquisition. Hillsdale, NJ, Erlbaum.
Petrushin, V. and Sinitsa, K. (1993) Using Probabilistic Techniques for Learning Modelling. Proceedings of AI-ED 93. Edinburgh, Scotland.
Bobrow, D. G. (1984) Qualitative Reasoning about Physical Systems. North Holland.
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Mihalis, P., Maria, G. (1995). An application of fuzzy logic to student modelling. In: Tinsley, J.D., van Weert, T.J. (eds) World Conference on Computers in Education VI. WCCE 1995. IFIP — The International Federation for Information Processing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-34844-5_10
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DOI: https://doi.org/10.1007/978-0-387-34844-5_10
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