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September 18, 2025British Journal of Educational Technology16 citations

Optimizing self‐regulated learning: A mixed‐methods study on GAI's impact on undergraduate task strategies and metacognition

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PWPing WangTLT.‐C. LiuYYYingying Yang

Key Points

  • Students using GAI tools showed greater improvements in task strategies and metacognitive awareness.
  • Quantitative analysis indicated experimental participants outperformed control peers in writing performance assessments.
  • Qualitative findings suggest GAI tools help facilitate metacognitive reflection and adaptive strategy use.
  • Concerns about over-reliance on GAI and content accuracy were highlighted by participants, indicating areas for caution.

Abstract

Abstract The integration of generative artificial intelligence (GAI) in education has shown the potential to improve learning outcomes, yet its impact on self‐regulated learning (SRL) in second language (L2) writing remains underexplored. This mixed‐methods study investigated the effects of a GAI chatbot tool on task strategy diversity, metacognitive awareness and writing performance among 40 undergraduate students in Eastern China over an 8‐week intervention. Participants were randomly assigned to an experimental group ( n = 20) using the GAI chatbot platform Tongyi.ai or a control group ( n = 20) relying on traditional resources. Data were collected using the Metacognitive Awareness Inventory (MAI), Strategy Inventory for Language Learning (SILL), writing performance assessments, participant interaction logs, reflective journals and semi‐structured interviews. Quantitative analysis revealed that the experimental group showed greater improvements in task strategy diversity, metacognitive awareness and writing performance than the control group. Qualitative analysis further indicated that GAI tools could facilitate task planning, promote adaptive strategy use and deepen metacognitive reflection. Despite these benefits, participants expressed concerns about the potential of over‐reliance on GAI and the accuracy of its generated content. The present study highlights the potential of GAI to enhance SRL in L2 writing by fostering adaptive task strategies and promoting metacognitive development, offering valuable implications for integrating GAI into L2 writing instruction. Practitioner notes What is already known about this topic Generative AI (GAI) tools have shown the potential to enhance various aspects of education, including personalized learning and feedback provision. Self‐regulated learning (SRL) is crucial for students' academic success, particularly in second language writing. Technology has been found to support the development of writing strategies and metacognitive skills. What this paper adds This study provides novel empirical evidence on how GAI tools influence undergraduate students' task strategies and metacognitive awareness in self‐regulated learning, specifically in L2 writing contexts. The research demonstrates that students using GAI tools developed more diverse and adaptive task strategies compared with those using traditional resources. The study reveals that GAI tool usage led to increased metacognitive awareness among students, enhancing their ability to plan, monitor and evaluate their writing processes. Implications for practice and policy Educators should consider integrating GAI tools into L2 writing instruction to support students' development of diverse task strategies and metacognitive skills. When implementing GAI in education, it is crucial to balance technology assistance with fostering students' independent thinking and creativity. Future research should explore the long‐term effects of GAI on self‐regulated learning and investigate its impact across different student populations and educational contexts. Educational institutions should develop guidelines for the ethical use of GAI tools in academic settings, addressing concerns about academic integrity and data privacy.

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Cite This Study

Wang et al. (2025) studied this question.

synapsesocial.com/papers/68d46ccf31b076d99fa69219https://doi.org/10.1111/bjet.70018
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