Abstract

The growing attractiveness of industry careers, driven in part by the Fourth Industrial Revolution (4IR), has led many Mathematical Sciences graduates to forgo postgraduate study. This trend has contributed to a shortage of expertise in PhD-level research supervision within Statistics departments in South Africa. A secondary challenge, which further strains the supervisory knowledge pipeline, is the large number of senior academics approaching retirement or who are already retired (Fabris-Rotelli et al., 2022).

In response to these challenges, the authors developed a guiding rubric to support early-career PhD supervisors in Statistics (Fabris-Rotelli et al., 2025). The rubric is formulated as a structured yet developmental framework for guiding both supervisors and PhD students throughout the doctoral journey. Rather than focusing primarily on the final thesis as a product, it foregrounds the student's development as an independent researcher through scholarly engagement, professional development, research integrity, critical thinking, and effective supervisory practice. It also aims to promote greater transparency, consistency, and scaffolded support during the development of the student into an independent researcher.

This presentation focuses on the conceptualisation and development of the guiding rubric, including the rationale for its structure and its potential application within Statistics and beyond. Although developed specifically for PhD supervision in Statistics in South Africa, the rubric offers a broader framework for teaching and learning in postgraduate education. It provides a practical approach to supporting doctoral development, strengthening supervisory practice, and navigating questions of academic integrity within an increasingly complex higher education environment.