Extensive Reading in the Age of Artificial Intelligence

Extensive reading (ER) has long been a foundational construct in second language acquisition (SLA) theory, due to its ability to foster implicit linguistic knowledge and improve fluency.Rooted in the principles of providing learners with abundant, comprehensible, and self-selected input, its implementation has often faced practical challenges related to resources and assessment.This article introduces the key construct of ER in the tech-driven, AI-powered era.Drawing on the seminal work by Day and Bamford (1998) as well as recent research on the primacy of input-based learning, we argue that AI does not render ER obsolete; rather, it offers vast opportunities to scale, personalize, and enhance ER programs.AI-powered tools can address traditional implementation challenges by facilitating content curation, providing adaptive scaffolding, and enabling more efficient monitoring.