Students' Reliance on AI Writing Tools in ESL/EFL Higher Education: A Systematic Review

The systematic review presented herein investigates the reliance of students on artificial intelligence (AI) writing tools within higher education contexts for English as a second or foreign language (ESL/EFL). This review synthesises evidence on use, trust, overreliance, writing proficiency, and critical-thinking skills. Using PRISMA-informed procedures, a search of the Scopus database from January 2023 to 20 August 2026 yielded 611 unique English-language records. These records met the empirical eligibility criteria. The resulting investigation is reported as a systematic metadata-and-abstract review, as the export was limited to metadata and abstracts rather than a complete full-text corpus. Tactical reliance predominates among the synthesised data. AI is frequently used for grammar, vocabulary, paraphrasing, ideation, outlining, feedback, and revision, whereas whole-text generation functions primarily as a substitutive mechanism. Usefulness, ease of use, self-efficacy, and accessibility strongly predict initial adoption. Trust, conversely, is consistently qualified by documented concerns regarding inaccurate information, generic feedback, privacy risks, potential plagiarism, and the attenuation of authorial voice. Immediate gains in surface accuracy, fluency, organisation, revision efficiency, confidence, and writing self-efficacy represent the most consistent outcomes of AI support. Outcomes related to critical thinking remain highly conditional. Reasoning is supported through verification, reflective prompting, and guided comparison; uncritical, frequent use, by contrast, encourages cognitive offloading, diminishes originality, and weakens authorial control. The educational value of these tools ultimately depends on the specific tasks delegated to the system, the rigor of verification practices, and the pedagogical retention of learner agency.

Artificial intelligence; AI writing tools; ESL; EFL; Reliance

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