Predicting Student Performance in Higher Education

D 2013

Predicting Student Performance in Higher Education

BYDŽOVSKÁ, Hana and Lubomír POPELÍNSKÝ

Basic information

Original name

Predicting Student Performance in Higher Education

Authors

BYDŽOVSKÁ, Hana (203 Czech Republic, belonging to the institution) and Lubomír POPELÍNSKÝ (203 Czech Republic, guarantor, belonging to the institution)

Edition

Neuveden, 24th International Workshop on Database and Expert Systems Applications - Dexa 2013, p. 141-145, 5 pp. 2013

Publisher

IEEE Computer Society

Other information

Language

English

Type of outcome

Proceedings paper

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

is not subject to a state or trade secret

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/13:00069109

Organization unit

Faculty of Informatics

ISBN

978-0-7695-5070-1

ISSN

DOI

http://dx.doi.org/10.1109/DEXA.2013.22

UT WoS

000335791800026

Keywords in English

student performance; recommender system; data mining; social network analysis

Abstract

In the original language

In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities.

Links

LG13010, research and development project

Name: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Acronym: ERCIM-CZ)

Investor: Ministry of Education, Youth and Sports of the CR

Cite

BYDŽOVSKÁ, Hana and Lubomír POPELÍNSKÝ. Predicting Student Performance in Higher Education. In Franck Morvan, A Min Tjoa, Roland R. Wagner. 24th International Workshop on Database and Expert Systems Applications - Dexa 2013. Neuveden: IEEE Computer Society, 2013, p. 141-145. ISBN 978-0-7695-5070-1. Available from: https://dx.doi.org/10.1109/DEXA.2013.22.

@inproceedings{1120454,
   author = {Bydžovská, Hana and Popelínský, Lubomír},
   address = {Neuveden},
   booktitle = {24th International Workshop on Database and Expert Systems Applications - Dexa 2013},
   doi = {http://dx.doi.org/10.1109/DEXA.2013.22},
   editor = {Franck Morvan, A Min Tjoa, Roland R. Wagner},
   keywords = {student performance; recommender system; data mining; social network analysis},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Neuveden},
   isbn = {978-0-7695-5070-1},
   pages = {141-145},
   publisher = {IEEE Computer Society},
   title = {Predicting Student Performance in Higher Education},
   year = {2013}
}

TY  - CONF
ID  - 1120454
AU  - Bydžovská, Hana - Popelínský, Lubomír
PY  - 2013
TI  - Predicting Student Performance in Higher Education
PB  - IEEE Computer Society
CY  - Neuveden
SN  - 9780769550701
KW  - student performance
KW  - recommender system
KW  - data mining
KW  - social network analysis
N2  - In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities.
ER  -

BYDŽOVSKÁ, Hana and Lubomír POPELÍNSKÝ. Predicting Student Performance in Higher Education. In Franck Morvan, A Min Tjoa, Roland R. Wagner. \textit{24th International Workshop on Database and Expert Systems Applications - Dexa 2013}. Neuveden: IEEE Computer Society, 2013, p.~141-145. ISBN~978-0-7695-5070-1. Available from: https://dx.doi.org/10.1109/DEXA.2013.22.

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