Teachers as Detectives? Professional Identity Conflict in the Era of Generative AI in Student Assessment

Abstract

Background: The rapid integration of generative artificial intelligence (AI) into higher education is transforming assessment practices and creating new challenges for EFL teachers. As generative AI becomes increasingly embedded in students’ academic tasks, EFL teachers face responsibility for identifying AI-generated content and maintaining academic integrity, thereby potentially shifting their role from facilitators toward “detectives” and contributing to identity conflict. Objective: This study examines how generative AI in assessment reshapes EFL teachers’ professional roles and identities, focusing on responsibility, cognitive workload, identity conflict, institutional ambiguity, and ethical concerns. Methods: Adopting an interpretivist paradigm, the study involved 15 EFL teachers. Data were collected through semi-structured interviews and analyzed thematically following Braun and Clarke’s (2006) framework. An abductive approach guided analysis through a four-dimensional conceptual model. Network analysis used Jaccard similarity and phi coefficients to examine thematic co-occurrence and association strength. Results: The findings show that AI is reshaping assessment and teacher roles through increased responsibility, cognitive workload, and identity conflict. Institutional ambiguity regarding AI policies was highly prevalent in co-occurrence, however, its relatively limited structural connectivity within the thematic network suggested that institutional ambiguity functioned primarily as a contextual condition shaping teachers’ experiences rather than as a central organizing factor. Stronger structural dynamics involved frustration, loss of control, demotivation, cognitive workload, and ethical–religious concerns regarding integrity, fairness, and guilt. Conclusion: The findings highlight the need to move beyond detection-oriented responses toward institutional approaches supporting AI literacy, assessment reform, and human–AI collaboration. Rather than positioning teachers primarily as AI detectors, institutions should support them in using AI as a collaborative thinking partner while preserving human judgment, creativity, critical engagement, and pedagogical responsibility.