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@inproceedings{1345298,
author = {Bydžovská, Hana},
address = {Raleigh, NC, USA},
booktitle = {Proceedings of the 9th International Conference on Educational Data Mining},
editor = {Tiffany Barnes, Min Chi, Mingyu Feng},
keywords = {course enrollment recommender system; student performance; prerequisites; university information system},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Raleigh, NC, USA},
pages = {312-317},
publisher = {International Educational Data Mining Society},
title = {Course Enrollment Recommender System},
year = {2016}
}
TY - JOUR
ID - 1345298
AU - Bydžovská, Hana
PY - 2016
TI - Course Enrollment Recommender System
PB - International Educational Data Mining Society
CY - Raleigh, NC, USA
KW - course enrollment recommender system
KW - student performance
KW - prerequisites
KW - university information system
N2 - One of the main problems faced by university students is to create and manage the semester course plan. In this paper, we present a course enrollment recommender system based on data mining techniques. The system mainly helps with students’ enrollment decisions. More specifically, it provides recommendation of selective and optional courses with respect to students’ skills, knowledge, interests and free time slots in their timetables. The system also warns students against difficult courses and reminds them mandatory study duties. We evaluate the usability of designed methods by analyzing real-world data obtained from the Information System of Masaryk University.
ER -
BYDŽOVSKÁ, Hana. Course Enrollment Recommender System. Online. In Tiffany Barnes, Min Chi, Mingyu Feng. \textit{Proceedings of the 9th International Conference on Educational Data Mining}. Raleigh, NC, USA: International Educational Data Mining Society, 2016, p.~312-317.
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