Australian researchers have piloted a new supervision model for doctoral and masters-level research students that places student experience at the center of program design. The Cohort-based Advisory Team (CAT) model applies design thinking methodology to improve how universities support Higher Degree by Research (HDR) students, who pursue research-focused postgraduate degrees.
The approach treats students as active collaborators rather than passive recipients of supervision. Researchers designed the CAT model by first empathizing with student challenges, a core principle of design thinking. This meant listening to what doctoral and masters candidates actually need from their advisory teams, rather than assuming traditional one-to-one supervision models work universally.
The CAT prototype brings together multiple advisors in structured cohorts. Instead of students relying solely on a single supervisor, they gain input from several experienced researchers and mentors working in concert. This arrangement addresses common HDR frustrations: isolation, inconsistent feedback, and bottlenecks when a primary supervisor becomes unavailable. Cohort-based structures also create peer learning opportunities, allowing students to learn from others navigating similar research challenges.
The model embeds work-based learning directly into postgraduate research education. Students engage in genuine research while developing professional skills tied to academic and research careers. This integration moves beyond classroom-based coursework to meaningful application.
Design thinking drives the entire architecture. Rather than imposing supervision structures based on tradition or administrative convenience, the researchers systematically identified pain points in the student experience and iterated solutions. This user-centered approach has grown increasingly common in higher education program redesign.
The CAT model addresses a persistent challenge in research education. Many HDR students report feeling unsupported, particularly during writing phases or when navigating complex methodology questions. Multiple advisors with different expertise can provide richer feedback and more coverage across the research lifecycle.
Universities testing this approach benefit from clearer frameworks for supporting postgraduate researchers while