Deep Learning Integration in ELT for Adolescent Learners in Indonesia

Artificial intelligence tools have considerable potential to support English language teaching in terms of personalized learning, instant feedback, authentic input, and opportunities for interactive practice outside the classroom. However, the value of AI is not only in the technology but also in the way teachers design, guide, monitor, and evaluate its use in meaningful learning activities. The successful implementation of AI requires teachers to balance technological innovation with pedagogical planning, ethical awareness, institutional readiness, and learner-centered instruction.

This study aims to explore how English teachers integrate AI tools in adolescent English language classrooms and to identify the main obstacles that impede effective AI integration. The barriers considered include access, cost, digital literacy, dependence on AI, data privacy, and assessment integrity.

A descriptive quantitative research design was used in this study. Data were collected through a questionnaire with closed-ended questions and statements on a Likert scale. The questionnaire covered teacher background, the type of AI tools used, the reasons for using AI, how often it was used, perceived benefits, and challenges in implementation. The research concerns English teachers who teach adolescent learners in formal educational settings, such as general and vocational high schools. The recommendation is to select five English teachers to participate in the questionnaire and observe three to five English lessons to gain insights into the use of AI in actual classroom practices. The data were analyzed by descriptive statistical methods such as frequency, percentage, mean, and standard deviation. The TPACK framework guides the study in investigating the relationship between technological, pedagogical, and content knowledge in AI-supported English instruction

It is expected that the study will identify patterns in teachers’ use of AI tools, such as the most common tools, reasons for use, perceived benefits, and main challenges.