Artificial Intelligence in Teaching EFL Reading: A Literature Review of Trends, Pedagogical Approaches, and Future Directions (2019–2025)

Abstract

ABSTRACT Background of study: The rapid growth of artificial intelligence (AI) has had a substantial impact on English as a Foreign Language (EFL) teaching, particularly reading instruction. In recent years, AI-based tools such as generative AI models, adaptive reading platforms, and automated feedback systems have been increasingly used in EFL courses to improve students' understanding, engagement, and motivation. Aims and scope of paper: The purpose of the study is to investigate the function of AI in aiding EFL reading teaching by conducting a complete systematic literature evaluation of empirical studies published between 2020 and 2025 in Scopus- and Sinta-indexed publications. Methods: The review compiles findings from fourteen peer-reviewed studies that examine the effectiveness, problems, and pedagogical implications of AI-assisted EFL reading instruction. Result: The study found that AI technologies improved learners' reading proficiency by delivering tailored learning paths, quick feedback, and interactive reading experiences. Furthermore, AI encourages learner autonomy, alleviates reading anxiety, and improves metacognitive awareness. However, some studies have identified problems, such as an overreliance on AI-generated content, ethical concerns about data privacy, and a lack of contextual sensitivity in EFL reading materials. Conclusion: In conclusion, while AI presents significant prospects for improving EFL reading pedagogy, it must be integrated critically and ethically into human-centered learning frameworks. The findings highlight the importance of teacher training, curricular alignment, and further empirical study into AI's long-term effects on reading comprehension and literacy development. This work adds to the expanding body of research calling for pedagogically sound and culturally appropriate AI applications in EFL education.

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