A Course Recommender System based on Graduating Attributes

Behdad Bakhshinategh, Gerasimos Spanakis, Osmar Zaiane, Samira ElAtia

2017

Abstract

Assessing learning outcomes for students in higher education institutes is an interesting task with many potential applications for all involved stakeholders (students, administrators, potential employers, etc.). In this paper, we propose a course recommendation system for students based on the assessment of their “graduate attributes” (i.e. attributes that describe the developing values of students). Students rate the improvement in their graduating attributes after a course is finished and a collaborative filtering algorithm is utilized in order to suggest courses that were taken by fellow students and rated in a similar way. An extension to weigh the most recent ratings as more important is included in the algorithm which is shown to have better accuracy than the baseline approach. Experimental results using correlation thresholding and the nearest neighbors approach show that such a recommendation system can be effective when an active neighborhood of 10-15 students is used and show that the numbers of users used can be decreased effectively to one fourth of the whole population for improving the performance of the algorithm.

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Paper Citation


in Harvard Style

Bakhshinategh B., Spanakis G., Zaiane O. and ElAtia S. (2017). A Course Recommender System based on Graduating Attributes . In Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-239-4, pages 347-354. DOI: 10.5220/0006318803470354


in Bibtex Style

@conference{csedu17,
author={Behdad Bakhshinategh and Gerasimos Spanakis and Osmar Zaiane and Samira ElAtia},
title={A Course Recommender System based on Graduating Attributes},
booktitle={Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2017},
pages={347-354},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006318803470354},
isbn={978-989-758-239-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - A Course Recommender System based on Graduating Attributes
SN - 978-989-758-239-4
AU - Bakhshinategh B.
AU - Spanakis G.
AU - Zaiane O.
AU - ElAtia S.
PY - 2017
SP - 347
EP - 354
DO - 10.5220/0006318803470354