Evaluation module based on Bayesian networks to Intelligent Tutoring Systems

Alan Ramírez-Noriega, Reyes Juárez-Ramírez and Yobani Martínez-Ramírez

International Journal of Information Management, 2017, vol. 37, issue 1, 1488-1498

Abstract: Assessing knowledge acquisition by the student is the primary task of an Intelligent Tutoring System (ITS). Assessment is needed to adapt learning materials and activities to student's capacities. In this paper, a proposal to infer the level of knowledge possessed by the student is presented. A general structure of an ITS is shown, an evaluation module based on Bayesian network is proposed. The module mainly based on a test was implemented to know what student knows. During the test, the software system chooses the new questions based on the responses to the previous ones, that is, the software system makes an adaption in real time. A network of concepts was used to get the inferences, which contains the relationships between concepts. Evaluation module could infer many questions and concepts through the relations and the probabilistic inference of the Bayesian network. It information easily can be used to reinforce weak topics in order to cover the student's needs. Given the positive evidence is considered that testing the rest of variable examined in the Bayesian network can provide better accurate in the diagnostic of student’ knowledge possession.

Keywords: Knowledge representation; Bayesian network; Evaluation; Intelligent Tutoring System (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:37:y:2017:i:1:p:1488-1498

DOI: 10.1016/j.ijinfomgt.2016.05.007

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