Cohort supervision and pedagogy in higher degree research: rethinking the dyadic model

Purpose This discussion article explores the pedagogical and institutional implications of cohort supervision in Higher Degree Research (HDR), challenging the traditional dyadic model. It aims to illuminate how cohort supervision can foster collaborative learning, enhance candidate wellbeing, support equity and inclusion, and democratize doctoral education. By examining diverse models and their implementation across global contexts, the article identifies key tensions and opportunities in transitioning to cohort-based supervision. It also considers how such models align with contemporary educational theories and institutional priorities, offering a timely reflection on supervision practices in a post-COVID academic landscape increasingly focused on inclusivity, efficiency, and scholarly community. Design The article adopts a discussion-based approach. The analysis is guided by Wegner’s theory of Communities of Practice and is organized around key themes: supervisory roles and authority, peer learning dynamics, identity formation, and institutional readiness. Through comparative insights, the paper highlights how cohort models are designed, facilitated, and experienced, offering valuable insights and discussion points. Findings Cohort supervision models offer significant benefits, including enhanced candidate engagement, reduced isolation, and improved academic identity formation. They promote collaborative scholarship and distribute supervisory responsibilities, but also introduce tensions around role clarity, peer dynamics, and institutional capacity. The success of these models depends on thoughtful design, structured facilitation, and robust institutional support. Challenges include inconsistent participation, expert dominance, and lack of formal policy. When well-supported, cohort models can improve completion rates and foster resilience. However, without strategic alignment and adequate resources, they risk becoming unsustainable or ineffective, particularly in digitally mediated or resource-constrained environments. Conclusion This article contributes a critical and timely rethinking of HDR supervision by positioning cohort models as transformative pedagogical strategies rather than mere logistical solutions. It advances the discourse by framing cohort supervision within democratic and collaborative learning paradigms, challenging entrenched norms of academic authority and individualism. By foregrounding the pedagogical potential of cohort models, it offers a fresh lens through which to view doctoral education; one that prioritizes community, reflexivity, and shared scholarly growth, and offers recommendations for institutions and supervisors.