Impostor-related experiences and generative AI in a Jordanian EFL writing course

This longitudinal qualitative multiple-case study examined how 24 undergraduate EFL students at a Jordanian public university experienced generative AI during a 12-week academic writing course. The multi-source dataset included successive drafts, archived ChatGPT interactions, decision logs, reflective journals, interviews, and stimulated-recall sessions. Reflexive thematic analysis was combined with episode-level tracing. Impostor phenomenon was used as a sensitizing lens rather than as a measured participant attribute. The findings showed that AI reduced immediate drafting and language difficulties but sometimes shifted uncertainty toward ownership, legitimacy, deservingness, and fear of exposure. Students did not treat AI as a consistently reliable authority; instead, they accepted, adapted, resisted, and, most frequently, verified its suggestions. Concerns about hidden expectations and imagined judgment were evident before a Kafka-focused mini-unit. After the unit, some students used terms such as hidden rules and invisible judges to express these concerns more clearly. The findings therefore suggest that Kafka provided a shared language for reflection rather than creating these concerns or causing changes in authorship. Overall, structured AI use supported more accountable textual decision-making while also generating new affective and authorship-related pressures.