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    Fuzzy inference for student diagnosis in adaptive educational hypermedia

    Grigoriadou, M. and Kornilakis, H. and Papanikolaou, K.A. and Magoulas, George (2002) Fuzzy inference for student diagnosis in adaptive educational hypermedia. In: Vlahavas, I.P. and Spyropoulos, C.D. (eds.) Methods and Applications of Artificial Intelligence: Second Hellenic Conference on AI. Lecture Notes in Computer Science 2308. Springer, pp. 191-202. ISBN 9783540434726.

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    Abstract

    In this paper we propose a method that implements student diagnosis in the context of the Adaptive Hypermedia Educational System INSPIRE - INtelligent System for Personalized Instruction in a Remote Environment. The method explores ideas from the fields of fuzzy logic and multicriteria decisionmaking in order to deal with uncertainty and incorporate in the system a more complete and accurate description of the expert’s knowledge as well as flexibility in student’s assessment. To be more precise, an inference system, using fuzzy logic and the Analytic Hierarchy Process to represent the knowledge of the teacher-expert on student’s diagnosis, analyzes student’s answers to questions of varying difficulty and importance, and estimates the student’s knowledge level. Preliminary experiments with real students indicate that the method is characterized by effectiveness in handling the uncertainty of student diagnosis, and is found to be closer to the assessment performed by a human teacher, when compared to a more traditional method of assessment.

    Metadata

    Item Type: Book Section
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 29 Jun 2021 13:52
    Last Modified: 29 Jun 2021 13:52
    URI: https://eprints.bbk.ac.uk/id/eprint/44921

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