Working memory in technology-enhanced language learning: a systematic review from interactive to AI-mediated contexts
Abstract
Introduction: Working memory (WM) is a central cognitive constraint in second and foreign language learning, particularly in technology-enhanced instructional environments. While pre-AI computer-assisted language learning (CALL) research has examined how interactive technologies interact with individual differences in WM capacity, the rapid emergence of AI-mediated language learning tools raises new questions about how WM demands are managed, redistributed, or compensated. This review examines how WM has been conceptualized and empirically addressed across two historical eras of language learning technology.
Methods: This systematic review adopts a PRISMA 2020-compliant historical-comparative design and synthesizes 31 primary empirical studies, including 27 studies from the Interactive Era (2010-2024) and 4 studies from the AI-Mediated Era (2024-2025), supplemented by recent systematic reviews and theoretical work. Studies were analyzed within two analytically distinct corpora, focusing on instructional design features, WM-related outcomes, cognitive load management, and measurement approaches, followed by cross-era comparison guided by three research questions.
Results: Interactive Era studies show that CALL, multimedia, and online platforms provide multimodal input, adaptive feedback, collaboration, and flexible pacing, but frequently induce cognitive overload and unequal learning outcomes associated with individual differences in WM capacity, which is typically treated as…
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