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@inproceedings{1355836,
author = {Bydžovská, Hana},
address = {Bratislava},
booktitle = {Proceedings in Informatics and Information Technologies},
editor = {Mária Bieliková, Ivan Srba},
keywords = {course similarity; student performance prediction; university information system},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Bratislava},
isbn = {978-80-227-4619-9},
pages = {65-68},
publisher = {WIKT & DaZ 2016},
title = {Course Similarity Analysis},
year = {2016}
}
TY - JOUR
ID - 1355836
AU - Bydžovská, Hana
PY - 2016
TI - Course Similarity Analysis
PB - WIKT & DaZ 2016
CY - Bratislava
SN - 9788022746199
KW - course similarity
KW - student performance prediction
KW - university information system
N2 - Courses offered to students at universities have different characteristics. In this paper, we analyse course similarities to improve the students’ performance prediction. We utilize the item-to-item collaborative filtering approach that computes course similarities based on students’ grades. We also use content based techniques to compute course similarities based on the information from the course catalogue, e.g. the course content or prerequisites. Using the computed similarities and utilizing different clustering algorithms, we are able to reveal interesting course groups that can be used to improve the student performance prediction. Finally, we are able to predict the students’ final grades of the investigated course by examining grades of only three related courses.
ER -
BYDŽOVSKÁ, Hana. Course Similarity Analysis. Online. In Mária Bieliková, Ivan Srba. \textit{Proceedings in Informatics and Information Technologies}. Bratislava: WIKT \&{} DaZ 2016, 2016, s.~65-68. ISBN~978-80-227-4619-9.
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