Toward an ecological systems approach to doctoral student resilience: qualitative evidence from the Covid-19 pandemic

Purpose This study aims to contribute to the growing body of literature documenting responses to short- and long-term impacts of the COVID-19 pandemic on doctoral students. This study examines support practices at different levels of the education system in which doctoral students are embedded, drawing on Bronfenbrenner’s ecological systems model to better understand how these contribute to doctoral students’ degree of resilience under stress. Design/methodology/approach Using online group interviews, this study explores the experiences of 21 doctoral students from seven universities across Europe, Africa and Asia. Findings The analysis revealed that the quality of supervisor support at the microsystem level was the most crucial factor determining how severely the doctoral students experienced negative impacts from the pandemic. However, broader institutional and systemic challenges – including inadequate online infrastructure and lack of incentives for additional mentoring – limited the support options available to students. In settings with fewer institutional resources, students exhibited adaptive resilience by actively seeking alternative sources of support at the mesosystem level, particularly through peer networks and external mentors. Originality/value This study extends the literature on resilience in higher education settings. This study applies Bronfenbrenner’s ecological systems model to understand doctoral students’ experiences during the COVID-19 pandemic. It illustrates how the model can help understand the sources of individual resilience that are facilitated at different levels of the support systems. This study uses a sample of doctoral students with diverse characteristics in personal situations. Based on the findings, the study provides policy recommendations and identifies venues for further research needed in the field to understand the longer-term impact of the pandemic across different regional settings.