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Authors: Hana Bydžovská and Lubomír Popelínský

Affiliation: Masaryk University, Czech Republic

Keyword(s): Recommender System, Social Network Analysis, Data Mining, Prediction, University Information System.

Related Ontology Subjects/Areas/Topics: Computer-Supported Education ; Information Technologies Supporting Learning ; Learning Analytics

Abstract: This paper focuses on recommendations of suitable courses for students. For a successful graduation, a student needs to obtain a minimum number of credits that depends on the field of study. Mandatory and selective courses are usually defined. Additionally, students can enrol in any optional course. Searching for interesting and achievable courses is time-consuming because it depends on individual specializations and interests. The aim of this research is to inspect different techniques how to recommend students such courses. This paper brings results of experiments with three approaches of predicting student success. The first one is based on mining study-related data and social network analysis. The second one explores only average grades of students. The last one aims at subgroup discovery for which prediction may be more reliable. Based on these findings we can recommend courses that students will pass with a high accuracy.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Bydžovská, H. and Popelínský, L. (2014). Course Recommendation from Social Data. In Proceedings of the 6th International Conference on Computer Supported Education - Volume 2: CSEDU; ISBN 978-989-758-020-8; ISSN 2184-5026, SciTePress, pages 268-275. DOI: 10.5220/0004840002680275

@conference{csedu14,
author={Hana Bydžovská. and Lubomír Popelínský.},
title={Course Recommendation from Social Data},
booktitle={Proceedings of the 6th International Conference on Computer Supported Education - Volume 2: CSEDU},
year={2014},
pages={268-275},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004840002680275},
isbn={978-989-758-020-8},
issn={2184-5026},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Computer Supported Education - Volume 2: CSEDU
TI - Course Recommendation from Social Data
SN - 978-989-758-020-8
IS - 2184-5026
AU - Bydžovská, H.
AU - Popelínský, L.
PY - 2014
SP - 268
EP - 275
DO - 10.5220/0004840002680275
PB - SciTePress