Development and validation of an integer linear programming model for the lecturer-to-course assignment problem
محورهای موضوعی : Design of ExperimentLone Seboni 1 , Kgalalelo Rakgomo 2 , Botshelo Mhalapitsa 3
1 - Mechanical Engineering Department, University of Botswana, Faculty of Engineering and Technology, Gaborone, Botswana
2 - Mechanical Engineering Department, University of Botswana, Faculty of Engineering and Technology, Gaborone, Botswana
3 - Mechanical Engineering Department, University of Botswana, Faculty of Engineering and Technology, Gaborone, Botswana
کلید واژه: Optimization, Integer linear programming, Delphi, Assignment, Workload,
چکیده مقاله :
This study developed and validated a formalized and robust integer linear programming (ILP) model to optimize the lecturer-to-course assignment problem (concerning balancing workload) for a university department that offers engineering programs. Questionnaire surveys with 4 groups of a total of 159 informants (10 lecturers, 1 head of department, 1 program coordinator, and 147 mechanical engineering students) were conducted. Enumeration was used for lecturers, the head of the department, and the program coordinator, whilst convenience sampling was used for students, with a response rate of 60%. A binary integer linear programming (ILP) model was developed by considering workload-related constraints such as class capacity, course contact hours, course credits, and the number of courses per lecturer. The ILP model was implemented in optimization software and the results were validated using the Delphi method. The results demonstrate the robustness and efficiency of the model in balancing workload by objectively (reducing biases) assigning under-utilized lecturers to more courses and over-utilized lecturers to fewer courses, in terms of simultaneously considering other workload-related variables, unlike existing studies. These results were used to instill a timely, formal, and consistent assignment approach that is fair and free from biases. The proposed model contributes to enhancing fairness and hence collective satisfaction of lecturers, program coordinators, and students, given a formalized, consistent, and timesaving assignment approach that considers other workload-related variables other than the number of courses per lecturer. Another contribution lies in a deeper understanding of a comprehensive range of factors that play a role in lecturer-to-course assignments for higher education institutions. Moreover, this study has implications for practice, given that other academic institutions may benefit from this work, in terms of policy considerations.
This study developed and validated a formalized and robust integer linear programming (ILP) model to optimize the lecturer-to-course assignment problem (concerning balancing workload) for a university department that offers engineering programs. Questionnaire surveys with 4 groups of a total of 159 informants (10 lecturers, 1 head of department, 1 program coordinator, and 147 mechanical engineering students) were conducted. Enumeration was used for lecturers, the head of the department, and the program coordinator, whilst convenience sampling was used for students, with a response rate of 60%. A binary integer linear programming (ILP) model was developed by considering workload-related constraints such as class capacity, course contact hours, course credits, and the number of courses per lecturer. The ILP model was implemented in optimization software and the results were validated using the Delphi method. The results demonstrate the robustness and efficiency of the model in balancing workload by objectively (reducing biases) assigning under-utilized lecturers to more courses and over-utilized lecturers to fewer courses, in terms of simultaneously considering other workload-related variables, unlike existing studies. These results were used to instill a timely, formal, and consistent assignment approach that is fair and free from biases. The proposed model contributes to enhancing fairness and hence collective satisfaction of lecturers, program coordinators, and students, given a formalized, consistent, and timesaving assignment approach that considers other workload-related variables other than the number of courses per lecturer. Another contribution lies in a deeper understanding of a comprehensive range of factors that play a role in lecturer-to-course assignments for higher education institutions. Moreover, this study has implications for practice, given that other academic institutions may benefit from this work, in terms of policy considerations.
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