The Supervisorship service has been developed with the feature to match students to supervisors based on psychological perceptions through multidimensional analysis of matching algorithms and the feature to track students’ progress.
This study explores the utilization of four distinct algorithms for the purpose of student-supervisor matching. A comprehensive evaluation of these algorithms is conducted, encompassing a variety of metrics including preference satisfaction, workload balance, time and space complexities, minimum and maximum workload, and compatibility scores which this work introduced.