Unpacking Second Language Motivation in AI-Mediated Contexts: A Scoping Review

Zihang Guo, Chili Li

Abstract

Amidst the rapid evolution and proliferation of artificial intelligence (AI) technologies, the convergence of AI with second language acquisition (SLA) is becoming increasingly salient and pervasive. To assess the existing research on second language (L2) motivation in AI contexts and determine implications for future research, the present study aims to present a scoping review of research on AI-mediated L2 motivation. Specifically, this study aims to explore the frequently adopted theoretical frameworks, the motivational effects of AI on various specific domains of EFL and the factors that may influence the effects of AI-integrated L2 motivation. Totally, 26 relevant peer-reviewed articles (2020-2025) were selected based on Web of Science (WoS) for further analysis, using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol (PRISMA-P). The results show that a) five major theoretical frameworks are primarily applied in L2 motivation in AI-mediated contexts, among which the self-determination theory (SDT) is the most frequently used; b) AI plays the facilitative and motivational role in varieties of language learning domains of L2, such as writing, speaking, vocabulary acquisition, grammar and translation; and c) three key factors influencing L2 motivation in AI-mediated learning are technical, psychological, and individual differences. Drawing upon these research findings, this review proposes prospective directions for the future exploration and practical application of AI in the realm of EFL (English as a Foreign Language) learning and teaching.

Keywords

AI-mediated context; artificial intelligence (AI); L2 motivation; second language learning; scoping review

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DOI: https://doi.org/10.20961/transling.v6i2.111429