MATRIX AND TENSOR FACTORIZATION FOR PREDICTING STUDENT PERFORMANCE

Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Alexandros Nanopoulos, Lars Schmidt-Thieme

Abstract

Recommender systems are widely used in many areas, especially in e-commerce. Recently, they are also applied in technology enhanced learning such as recommending resources (e.g. papers, books,...) to the learners (students). In this study, we propose using state-of-the-art recommender system techniques for predicting student performance. We introduce and formulate the problem of predicting student performance in the context of recommender systems. We present the matrix factorization method, known as most effective recommendation approaches, to implicitly take into account the latent factors, e.g. “slip” and “guess”, in predicting student performance. Moreover, the knowledge of the learners has been improved over the time, thus, we propose tensor factorization methods to take the temporal effect into account. Experimental results show that the proposed approaches can improve the prediction results.

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Paper Citation


in Harvard Style

Thai-Nghe N., Drumond L., Horváth T., Nanopoulos A. and Schmidt-Thieme L. (2011). MATRIX AND TENSOR FACTORIZATION FOR PREDICTING STUDENT PERFORMANCE . In Proceedings of the 3rd International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-8425-49-2, pages 69-78. DOI: 10.5220/0003328700690078


in Bibtex Style

@conference{csedu11,
author={Nguyen Thai-Nghe and Lucas Drumond and Tomáš Horváth and Alexandros Nanopoulos and Lars Schmidt-Thieme},
title={MATRIX AND TENSOR FACTORIZATION FOR PREDICTING STUDENT PERFORMANCE},
booktitle={Proceedings of the 3rd International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2011},
pages={69-78},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003328700690078},
isbn={978-989-8425-49-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - MATRIX AND TENSOR FACTORIZATION FOR PREDICTING STUDENT PERFORMANCE
SN - 978-989-8425-49-2
AU - Thai-Nghe N.
AU - Drumond L.
AU - Horváth T.
AU - Nanopoulos A.
AU - Schmidt-Thieme L.
PY - 2011
SP - 69
EP - 78
DO - 10.5220/0003328700690078