Mapping Iranian EFL Teachers’ Perceptions of AI-Enhanced Teaching Tasks: Insights through TPACK and CBAM Frameworks

کد مقاله : 1218-ELTCONF7.

نویسندگان

حمیده نامی انرجان *1، حسن سودمند افشار2 1دانشجو 2استاد

چکیده مقاله

This qualitative study explored Iranian English as a Foreign Language (EFL) teachers' perceptions of using Artificial Intelligence (AI) in teaching tasks. 33 Iranian EFL teachers participated in semi-structured interviews. Data were analyzed through thematic analysis through The Technological Pedagogical Content Knowledge (TPACK) and Stages of Concerns (SoC) components of Concerns-Based Adoption Model (CBAM) theoretical framework. This analysis yielded 33 open codes grouped into 12 sub-categories and subsequently into 4 super-categories. The findings indicated that teachers mostly consider AI as a time-saver and creativity-booster, but its applications for creating personalized learning material have not received enough attention due to structural inefficacies. SoC analysis indicated that more than 45 percent of the concerns stated by teachers were about organizational, infrastructural, and identity issues. These concerns fall into SoC stages 2 and 3, which deal with personal and managerial worries. These concerns affected EFL teachers focus on TPACK components. Analysis from TPACK perspective showed emerging Technological Content Knowledge (TCK) in using AI for content generation, but limited Technological Pedagogical Knowledge (TPK) and almost absent integrated TPACK. These findings can be useful for teacher trainers, education policymakers, and institutional leaders. Especially in educational environments where limited resources and Infrastructure deficiencies make technology integration more complex.

کلیدواژه ها

Artificial Intelligence, EFL teacher, TPACK, CBAM, Stages of Concern, Teacher Perceptions

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