A Research Supervision Framework for Quality and Scalability

Academic staff provide research supervision based on the one on one approach or the apprenticeship model. Current student recruitment policies are enrolling larger numbers of students on taught master’s programmes. The current research supervision approach is not sustainable with growing numbers of students and conducting research supervision that is scalable is a challenge. Increasing the number of supervisors leads to difficulties with the consistency in the quality of the supervision. This research proposes a research supervision framework that scales with increasing numbers of re-search students and ensures consistency in the quality of research supervision among faculty. The framework combines teaching practices, timetabled group supervision, co supervision, coaching and scaffolding. The research supervision framework was applied in timetabled group research supervision sessions in May to August2020 with 15 students, September 2020 to January 2021 with 10students and May to August 2021 with 12 students. Results demonstrate an increase in the quality of research as demonstrated by the publication of 4 book chapters, 3 peer reviewed international conference papers and 3 invention disclosures. These publications occur during a period of growth in student numbers by approximately 1000% from 2012 to 2020. This research is of interest to both Deans and faculty. Deans will gain insight in how to ensure quality of supervision with growing student numbers on taught master’s programmes. Faculty will gain insight in how to effectively supervise students in order to increase their academic publications using alternative supervision approaches.