AI-assisted writing's differential impact on EFL learners and implications for adaptive instruction
DOI:
https://doi.org/10.47989/ir31iConf64196Keywords:
AI-assisted writing, Human-AI interaction, Writing performance, Educational AIAbstract
Introduction. While AI-assisted writing tools gain widespread educational adoption, their differential impacts on English as a foreign language (EFL) learners across proficiency levels remain underexplored. This study investigates how AI writing assistance affects EFL learners at different proficiency levels to inform differentiated instructional design.
Method. A controlled experiment with 17 Chinese university students divided into low-, intermediate-, and high-proficiency groups employed mixed methods, analyzing 85 writing samples and 56 human-AI interaction dialogues using SPSS and NVivo.
Analysis. Findings revealed striking proficiency-dependent effects: low-proficiency learners showed significant writing improvements after AI-assisted training, while intermediate- and high-proficiency learners demonstrated minimal gains. Interaction analysis uncovered distinct usage patterns—low- and intermediate-proficiency learners relied on AI primarily for linguistic compensation, whereas high-proficiency learners engaged in extensive prompt refinement to align AI output with their writing goals.
Conclusion(s). Results challenge one-size-fits-all approaches to AI writing instruction. Current AI tools excel at addressing basic linguistic needs but struggle with higher-order writing skills required by advanced learners. Findings emphasise the need for proficiency-responsive AI interventions and enhanced explainability to transform AI assistance into sustainable writing competence.
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Copyright (c) 2026 Shaobo Liang , Yingyu Wang , Dan Wu
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