A Guiding Rubric for the Early-Career Doctoral Supervisor in Statistics

Proceedings of The 6th International Academic Conference on Education

Year: 2023

DOI: https://www.doi.org/10.33422/6th.iaceducation.2023.03.103


A Guiding Rubric for the Early-Career Doctoral Supervisor in Statistics

Michael J. von Maltitz, Inger Fabris-Rotelli, Ansie Smit, Danielle Roberts, Sonali Das, Daniel Maposa




Industry attracts statistical science graduates away from academia, and from the pursuit of further postgraduate studies. In South Africa, the industry draw has resulted in an academic capacity-building crisis within statistical sciences, with two primary factors exacerbating the move away from academia. First, academic salaries in statistical sciences are not comparable to that of industry at the same level of qualification (especially with the growth of ‘Data Science’). Second, the lack of sufficient supervisory skills and capacity, especially at doctoral level, is evident across South African Statistics departments. The discussions previously documented by the authors show that there is an urgent need for guidelines to support active early-career doctoral supervisors in South Africa. In this paper, we present a guiding rubric that has evolved from numerous discussions within a focus group of novice supervisors from South Africa. While this guiding rubric is by no means presented as a prescriptive set of rules, it aims to be a dynamic document that can be referred to by both the novice supervisor and the doctoral candidate to ameliorate potential stresses during the doctoral journey.

keywords: Doctoral supervision, postgraduate research, statistical sciences, South Africa, data science