Integrating Deep Learning and AI in CLT-Based English Course Design: A Qualitative Study of EFL Tutors - Yahya, Aliya Izet Begovic; Surwiti, Surwiti; Hasbullah, Hasbullah; Musliman, Acep; Syamsudin, Oom Rohmah (Teacher Training and Education Faculty of Syekh-Yusuf Islamic University Tangerang, 2025)
This study aims to explore how English tutors at the New Concept English Education Centre course institution integrate Artificial Intelligence (AI) technology and deep learning approaches in Communicative Language Teaching (CLT)-based learning planning. Using a qualitative approach with an exploratory case study design, data was collected through in-depth interviews, document studies, and classroom observations of 20 tutors who had participated in AI training. The results show that tutors understand the strategic role of AI in designing communicative, adaptive, and personalized learning. Tutors leverage various AI tools such as ChatGPT, Grammarly, and simulation videos to develop interactive speaking-based modules. This integration has a positive impact on increasing student engagement and the technological literacy of tutors. This research makes a theoretical and practical contribution to the development of technology-based learning models in the non-formal course sector, as well as encouraging tutors to be more adaptive to digital transformation in English language education.