AI-enhanced extensive reading: Empowering learners as content creators

Abstract

[EN] Extensive Reading (ER) is a well-established approach to second language acquisition, emphasising large volumes of enjoyable, comprehensible input. Despite its documented benefits for reading fluency, vocabulary growth, and learner motivation, ER programmes face persistent challenges, including limited access to graded materials, difficulty maintaining learner engagement, and constraints in tailoring content to individual needs. This paper introduces Extensive Reading and AI (ERAI), a prototype platform that integrates generative artificial intelligence to support ER pedagogy. ERAI enables the rapid creation of level-appropriate reading texts, customised for learners’ interests, cultural contexts, and linguistic profiles, while maintaining the repetition and language control necessary for sustained acquisition. The paper situates ERAI within established definitions of ER and reviews relevant research on reading processes and individual differences. Particular attention is given to issues of motivation, accessibility, and the alignment of AI-generated materials with ER principles. While empirical evaluation remains ongoing, ERAI demonstrates how emerging technologies may address current ER limitations and expand its reach to a broader population of language learners. The paper concludes by identifying future directions for research, including evaluation of learning outcomes, data privacy considerations, and cross-linguistic implementation.