Fuzzy Inference for Student Diagnosis in Adaptive Educational Hypermedia

Abstract

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.

Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

“…The following section shows a sample reference list with entries for journal articles [1], an LNCS chapter [2], a book [3], proceedings without editors [4] and [5], as well as a URL [6]. Please note that proceedings published in LNCS are not cited with their full titles, but with their acronyms!…”

“…But in order for that to be achieved, the knowledge as well as the experience of the educational expert has to be represented in a precise way and most important, the inference process used by the expert must be modelled and simulated [4].…”

“…Via those technologies the results are impressive even in cases where data is extremely vague and subjective [16]. Grigoriadou et al (2002) have attempted to achieve precise student diagnosis incorporating fuzzy logic and multicriteria decision-making in INSPIRE (Intelligent System for Personalized Instruction in a Remote Environment), a web -based AEHS (Adaptive Educational Hypermedia System -Brusilovsky, [43]). Via this combination, enhancement of adaptability of INSPIRE is being achieved.…”

“…The authors focus on student's diagnostic module which aims at student's classification according to his knowledge level and learning style. The method described has been tested over 20 postgraduate students of the Department of Informatics and Telecommunications of the University of Athens and proved to offer students' assessment as much reliable as the one performed by a human teacher [4].…”

Decade review (1999-2009): progress of application of artificial intelligence tools in student diagnosis

“…But in order for that to be achieved, the knowledge as well as the experience of the educational expert has to be represented in a precise way, and most importantly, the inference process used by the expert must be modelled and simulated (Grigoriadou et al, 2002).…”