Prediction of student actions using weighted Markov models

Huang, Xiaodi and Yong, Jianming and Li, Jiuyong and Gao, Junbin (2008) Prediction of student actions using weighted Markov models. In: ITME 2008: IEEE International Symposium on IT in Medicine and Education , 12-14 Dec 2008, Xiamen, China.

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Abstract

The Markov model has been applied to many prediction applications including the student models of intelligent tutoring systems. In this paper, we extend this well-known model to the weighted Markov model, and then apply it to student models in order to predict student behaviors. The prediction using our models is based not only on the frequency of collective behaviors of previous users, but also on the degrees of the relations between the predicted user and others. In doing so, a novel way is presented to quantify the similarities between previous students and the current active student. These similarity scores will be used as weights in the weighted Markov model.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published version deposited in accordance with the copyright policy of the publisher. © 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purpose or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Depositing User: Dr Jianming Yong
Faculty / Department / School: Historic - Faculty of Business - School of Information Systems
Date Deposited: 13 Oct 2009 03:11
Last Modified: 02 Jul 2013 23:25
Uncontrolled Keywords: weighted Markov model; prediction; student behaviour
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Identification Number or DOI: doi: 10.1109/ITME.2008.4743842
URI: http://eprints.usq.edu.au/id/eprint/5838

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