Hope and fear in AI-based language teaching: opportunities, challenges, and emotions

Abstract

The integration of artificial intelligence (AI) into second and foreign language (L2) education has increased significantly; however, its emotional impact on teachers remains underexplored, particularly in less commonly taught languages (LCTL) such as Turkish. This qualitative exploratory case study examines the perceptions, experiences, and emotional responses of 17 Turkish as a Foreign Language (TFL) teachers. Data were collected through semi-structured interviews and analyzed using reflexive thematic analysis assisted by MAXQDA 24 software, grounded in Pekrun's Control-Value Theory (CVT). Findings reveal a nuanced landscape where AI acts as a "pedagogical co-instructor." Teachers reported predominantly positive emotional responses, including feeling motivational (42.31%) and developer/beneficial (34.62%), while a minority expressed fear (7.69%) and suspicion (3.85%). These emotions are linked to perceived pedagogical control and the "English-centric" bias of current AI tools. The study concludes that successful AI integration in TFL requires balancing technological efficiency with human-centered cultural nuances.