ARTIFICIAL INTELLIGENCE FOR DEEP LEARNING IN ELT CLASSROOMS: INSIGHTS FROM A NATIONAL SURVEY OF INDONESIAN TEACHERS
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This study explores Indonesian EFL teachers’ knowledge, attitudes, and practices (KAP) regarding the integration of Artificial Intelligence (AI) in English Language Teaching (ELT) within the framework of deep learning. Employing a convergent mixed-methods design, data were collected from 675 Indonesian EFL teachers across various educational levels and provinces via an online questionnaire. In addition, 40 participants were purposively selected from the survey sample for focus group discussions to ensure data triangulation. Findings indicate that teachers generally have limited technical knowledge and familiarity with AI but hold positive beliefs about its potential to enhance the development of materials, reduce workload, and support personalized learning. Classroom practices, however, remain fragmented and efficiency-oriented, with AI often used for lesson preparation rather than transformative pedagogy. A strong demand for professional development emerged, highlighting the need for systematic AI training. This study contributes to the growing body of literature on AI in EFL contexts by proposing a Holistic Implication Model, grounded in the Knowledge, Attitude, and Practice (KAP) framework, which synthesizes how limited technical literacy and positive teacher beliefs converge to shape classroom integration, offering actionable insights for teacher training, curriculum reform, and policy development.
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