FACULTY MEMBERS’ EXPERIENCES WITH AI IN LANGUAGE TEACHING: A PEDAGOGICAL PERSPECTIVE
The rapid expansion of artificial intelligence (AI) in language education has created new expectations for educators while simultaneously introducing pedagogical, institutional, and professional challenges. However, existing research has predominantly focused on technological tool effectiveness and learner outcomes, leaving faculty members’ lived experiences and instructional adaptations comparatively underexplored. This study aims to explore faculty members’ experiences with AI in higher education language teaching and to examine the difficulties they encounter when integrating these technologies into instructional practices in pedagogically meaningful ways. The study employed a qualitative research design to examine participants’ experiences and the challenges they encountered. Participants were 12 faculty members working at Schools of Foreign Languages in three public universities in Türkiye. Data were collected through semi-structured interviews focusing on AI use, instructional practices, institutional conditions, and professional perceptions. The interviews were transcribed and analysed using thematic analysis to identify recurring patterns and shared experiences related to AI-supported teaching. The findings revealed a clear gap between technological familiarity and pedagogical integration. Although faculty members reported being able to use AI tools functionally for preparation, material development, and productivity-related tasks, they experienced difficulties in aligning these tools with learning outcomes, classroom interaction, and assessment practices. Institutional constraints, limited infrastructural support, workload pressures, ethical concerns, and varying levels of student readiness further shaped their engagement with AI-supported instruction. The results also indicated that AI integration influences teachers’ professional roles, creating tensions related to authority, control, and professional identity in technology-mediated learning environments. Overall, the study suggests that effective AI integration requires more than technical competence; it demands pedagogical guidance, institutional coordination, and the development of AI literacy among both educators and students. The findings have implications for teacher education, professional development, and institutional policy, emphasising the need for structured support, discipline-sensitive instructional models, and clear ethical frameworks. Future research should focus on developing pedagogically grounded AI practices and institutional strategies that enable sustainable and context-responsive integration of AI in language education.