Unveiling Supervisor‐Student Interactions: Patterns, Fluctuations, and Influencing Factors of Chinese Postgraduate EFL Learners’ Online Interaction With the Supervisor

ABSTRACT Informed by complex dynamic systems theory (CDST), this study investigated how Chinese postgraduate EFL learners interacted with their supervisor over six online supervisory sessions conducted via Tencent Meeting. Data sources included video‐recorded TLIs and narrative accounts (reflective journals, semi‐structured interviews, and student narratives). Quantitative state space grids (SSGs) and qualitative interpretative phenomenological analysis (IPA) were performed, which revealed the patterns of supervisory interactions characterized by closed teacher questions followed by short student responses, with considerable variability in interaction patterns over time. These patterns and variability of supervisory interactions were further found in relation to three clusters of factors (teacher support, learner attributes, and contextual affordances). The findings of this study suggest that supervisors need to diversify their questioning strategies and foster more dialogic engagement in online supervision. The study also highlights the value of combining SSGs and IPA for capturing real‐time interaction dynamics in digitally mediated contexts.