Evaluating AI's impact on self-regulated language learning: A systematic review

Abstract

AI technology is reshaping language classrooms, prompting students to adopt flexible roles exhibiting linguistic competence and self-regulated learning (SRL) skills. Considerable studies explore the necessary integrated learning perspectives, emphasizing AI's adaptive role as a mind tool. In AI-mediated language learning, the technology's metacognitive importance enables students to learn with AI as a partner, encouraging independent critical thinking. Within Zimmerman's SRL model, AI as a mind tool is integrated for improving language students' strategic employment in a cyclical process. A systematic review, following PRISMA protocols, examines the intersection of AI and self-regulated language learning (SRLL) over 2000–2022. Findings highlight AI's evolving role, predominantly through algorithms and systems, aiming for micro and macro integration. Interactive AI has not fully engaged in two-way directions, despite a familiar process approach in reviewed studies. In the favored ESL/EFL research context, task-specific AI is utilized to encourage cyclical improvement with learner autonomy enhancement mainly among higher education students at intermediate level or above. Pedagogical values are possible when major SRL phases are fully practiced, even without highly autonomous AI. Future research is directed toward adaptive personalized technology by exploring the dynamic interplay between AI technologies and SRLL as educational practices under Education 4.0 principles.