BAYESIAN NETWORK BASED ON FUZZY LOGIC IN EDUCATIONAL INTELLIGENT SYSTEMS

Afaf Adabashi, Meltem Eryılmaz

Abstract


A Web-based Intelligent Tutoring System is an educational platform that supports the teaching process with the aim of helping students navigate through the online course materials in order to achieve their learning goals. It has an ability to adapt an e-learning system to each individual learner according to his/her characteristics including the knowledge level, which usually come from uncertain information. Artificial intelligence techniques such as fuzzy logic and Bayesian networks are widely used to address uncertainty problems facing the intelligent tutoring systems. This research paper contributed to the field of research by developing an intelligent tutoring system, called FB-ITS using a combination of both the Bayesian network and fuzzy logic in order to support students in learning Excel. The system is validated and evaluated using an empirical method where the pre-test and post-test experiment was conducted in order to determine its effectiveness in providing learning to students. An experiment with 20 participants from undergraduate students yields positive results. It indicates that adapting learning material according to a knowledge level using a combination of Bayesian and fuzzy logic leads to better learning performance than using only the Bayesian network.

Keywords


Intelligent tutoring system, Bayesian networks, fuzzy logic, learning performance.

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References


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