文章基本信息

标题：Collaborative Course Assignment Problem to Minimize Unserved Classes and Optimize Education Quality
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作者：Purba Daru Kusuma ; Ratna Astuti Nugrahaeni
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2022
卷号：13
期号：4
DOI：10.14569/IJACSA.2022.0130421
语种：English
出版社：Science and Information Society (SAI)
摘要：This work proposes a collaborative course assignment model among universities. It is different from existing studies in educational assignment problems or course timetabling, where the scope is only within the institution or department. In this work, the system consists of several universities. A collaborative approach is conducted so that lecturers exchange is possible and conducted automatically. Each university shares its courses and lecturers. The optimization is conducted to minimize the unserved classes and improve education quality. The cloud-theory based simulated annealing is deployed to optimize the assignment. This model is then benchmarked with two non-collaborative models. The first model’s objective is to minimize the unserved classes only. The second model’s objectives are to minimize the unserved classes and improve education quality. The simulation result shows that the proposed assignment model is better in minimizing the unserved classes and improving education quality. The proposed model reduces 89 to 92 percent of the unserved classes ratio compared with the non-collaborative model.
关键词：Course assignment problem; simulated annealing; collaborative model; online teaching; combinatorial problem