생성형 AI 기반 교육 환경에서 영어 교사의 교수 동기에 대한 질적 연구

[김태영]

Kim, Tae-Young, & Hong, Somi. (2026). EFL teachers’ teaching motivation in generative AI-integrated classrooms: A qualitative study. English Language Teaching, 38(2), 115-141. 

This study investigates how generative artificial intelligence (GenAI) and AI-based digital textbooks (AIDT) influence English teachers’ teaching motivation and demotivation, as well as their instructional experiences and professional identity perceptions, in the Korean public education context. A qualitative approach was employed, drawing on semi-structured interviews with teachers across different school levels to capture their lived experiences of AI integration in classroom. Findings reveal that AI enhanced teaching motivation by reducing classroom anxiety, fostering confidence, and creating opportunities for innovative lesson design. Teachers emphasized that adapting texts, incorporating real-world issues, and personalizing materials for diverse learners increased both professional identity and student-teacher engagement. Such experiences reflect the fulfillment of competence and relatedness needs. Moreover, the use of AI expanded teachers’ sense of instructional efficacy, while also generating new challenges such as device management, technical setup, and the need of establishing assessment rubric for students’ assignment assisted by AI tools. The findings also highlighted that teachers redefined their roles from English-language knowledge transmitters to learning facilitators and advisors, though concerns about professional deskilling and identity crisis persisted. Overall, AI served double-edged functions simultaneously destabilizing and re-establishing teachers’ teaching motivation, instructional experiences, and professional identity perceptions. (193 words)

Key words: generative artificial intelligence (GenAI), digital textbooks, English teachers, teaching motivation, demotivation

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