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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, s.~312-317.
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