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Lecturer-Course Assignment Model in National Joint Courses Program to Improve Education Quality and Lecturers’ Time Preference.

Authors :
Kusuma, Purba Daru
Adiputra, Dimas
Source :
International Journal of Intelligent Engineering & Systems; 2022, Vol. 15 Issue 1, p361-369, 9p
Publication Year :
2022

Abstract

One critical problem in Indonesia's national joint courses program, initiated by the ministry of education and culture of Indonesia, is the lecturer-course assignment problem. Although the lecturer-course assignment problem has been studied widely as part of the education timetabling problem, no existing lecturer-course assignment model suits this circumstance. The new cases in this program are as follows. First, this program is conducted online. Second, the participants are students and lecturers from different universities. Based on this problem, this work proposes a novel lecturer-course assignment model that suits this program. The lecturers' preferred courses and timeslots become hard constraints. The model has three objectives: (1) maximizing the educational quality, (2) maximizing the lecturers' time preference, and (3) minimizing the number of unserved classes. This model is developed by using integer linear programming and optimized by using cloud theory-based simulated annealing. This proposed model is then compared with the four previous lecturers-course assignment models. The first model concerns about minimizing the number of unserved classes, while the second model focuses on maximizing the education quality. The maximum number of classes per course for every lecturer is considered in the third model while balancing the lecturer’s load (teach, research, community service) is the feature of the fourth model. The research concludes that the proposed model is appropriate for lecture-course assignment in Indonesia’s national joint courses program compared to the previous models. Based on the simulation result, the proposed model performs moderately in education quality and several unserved classes. Meanwhile, the proposed model is the best in the timeslot preference aspect by creating a 25% to 28% higher total timeslot score than other previous models. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2185310X
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
International Journal of Intelligent Engineering & Systems
Publication Type :
Academic Journal
Accession number :
154446606
Full Text :
https://doi.org/10.22266/ijies2022.0228.33