EFL Teachers' Engagement and Perceptions of Integrating Gemini AI for Professional Development - Aulia Khairunnisa Lubis; Ernita Daulay; Ahmad Amin Dalimunthe (IDEAS: Journal on English Language Teaching and Learning, Linguistics and Literature, 2026)
The rapid evolution of generative artificial intelligence (AI) has necessitated a shift in teacher professional development. However, a significant gap remains in understanding how language educators in traditional Islamic secondary schools navigate technological adoption amidst demanding administrative workloads. This study aimed to investigate EFL teachers' engagement—defined operationally through their behavioral prompt iterations and cognitive commitment—and their perceptions of integrating Gemini AI for professional development at a public Islamic high school (MAN) in Medan. Employing a descriptive qualitative approach, data were collected through methodological triangulation, including non-participant observations, semi-structured interviews, and artifact analysis of teaching modules produced by five purposively selected English teachers. The results indicated a high level of behavioral and cognitive engagement, where the application of Gemini AI reduced teaching module development time by approximately 80%. This figure was determined by comparing the teachers' average manual drafting time of 3 to 4 hours against the AI-assisted completion time of under 45 minutes. Furthermore, the integration enhanced the pedagogical quality of enrichment materials and student worksheets (LKPD) through Higher-Order Thinking Skills (HOTS) alignment. Despite initial technology-related anxiety among senior educators, participants perceived Gemini AI as an efficient supportive tool that minimizes administrative burdens and fosters instructional creativity. The study concludes that while Gemini AI effectively streamlines the structural implementation of the Independent Curriculum (Kurikulum Merdeka) in a Madrasah context, tailored peer-mentoring remains vital to address the intergenerational digital divide. These findings imply that structured AI integration can successfully enhance lesson-planning efficiency while respecting local educational structures.