Prediction of Student Actions Using Weighted Markov Model

Xiaodi Huang, Jianming Yong, Jiuyong Li, Junbin Gao

Research output: Book chapter/Published conference paperConference paper

4 Citations (Scopus)
5 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationITME 2008
EditorsRamana Reddy
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages154-159
Number of pages6
ISBN (Electronic)9781424436163
DOIs
Publication statusPublished - 2008
EventIEEE International Symposium on IT in Medicine and Education - Xiamen, China, China
Duration: 12 Dec 200814 Dec 2008

Conference

ConferenceIEEE International Symposium on IT in Medicine and Education
CountryChina
Period12/12/0814/12/08

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  • Cite this

    Huang, X., Yong, J., Li, J., & Gao, J. (2008). Prediction of Student Actions Using Weighted Markov Model. In R. Reddy (Ed.), ITME 2008 (pp. 154-159). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ITME.2008.4743842