An Optimization Model for the Student-to-Project Supervisor Assignment Problem-The Case of an Engineering Department. (31st October 2022)

• Record Type: Journal Article
• Authors: Ramotsisi, Johnson; Kgomotso, Mompoloki; Seboni, Lone
• Other Names: Salahi Maziar Academic Editor.
• Is Part Of: Journal of optimization. Volume 2022(2022)
• Publication Date: 2022-10-31
• Subjects: Mathematical optimization -- Periodicals; Structural optimization -- Periodicals; Mathematical optimization; Structural optimization; Periodicals; Electronic journals; 519.6
• DOI: 10.1155/2022/9415210
• Languages: English
• ISSNs: 2356-752X

Abstract

Abstract : Purpose . Empirical studies on the topic of assigning university project students to supervisors are currently underexplored. Such studies are critical to success of both the students and the university. Whilst extant research on this topic has contributed to an understanding of student assignments, what appears to be missing is application of a comprehensive framework to inform formulation and validation of a robust solution approach that takes account of both student and supervisor preferences, to optimize a real-life student-to-project supervisor assignment problem. Methodology . Questionnaire and interview surveys with project coordinators, project supervisors, head of department and students were conducted to identify factors surrounding the student-to-project supervisor assignment, through a case study approach in a university department offering engineering degree programs. This study not only develops a framework to understand an effective student-to-project supervisor assignment decision but also applies it in practice, through a case study in a University department offering engineering degree programs. An integer linear programming model was developed and implemented in an optimization software to optimize the student-to-project supervisor assignment, using data from the case study. Findings . Using OpenSolver, validated model results show improvements in matching both students and project supervisors' preferences, whilst complying with supervisors' workloads. These results also reveal an improvement in minimizing the project coordinator's time in doing the assignment by introducing a standardized approach that concurrently considers all variables in a consistent manner. Originality . The contribution lies in: (1) development of a robust framework for student-to-supervisor assignments, (2) explicit consideration of contextual factors that recognize different assignment scenarios, (3) identification of feedback loops to recognize not only the need for continuous improvement in student-to-supervisor assignments but also links to performance in final year projects, (4) unique insights to guide project coordinators in relation to an efficient, effective, comprehensive, and standardized approach to the student-to-project supervisor assignment, and (5) a deeper understanding of a comprehensive range of factors that play a role in student-to-project supervisor assignments in higher education institutions.