AI-Mediated Writing Instruction in Higher Education: A Systematic Review of Empirical Evidence

AI in EFL Writing Instruction: A Systematic Review of Writing Conceptualizations and Learner Agency

The findings revealed that learner agency is influenced more by pedagogical integration than by the technology itself, which underlined the importance of teaching EFL writing through theoretically informed, process-oriented approaches that empower learners and incorporate effective AI use.

Artificial Intelligence for Academic Writing and Speaking in Higher Education: A Systematic Review and the Mediated AI-Pedagogy Cycle

Artificial intelligence (AI) is increasingly shaping higher education, particularly in the development of academic writing and speaking skills. While AI tools offer immediate feedback and personalized learning opportunities, existing research often focuses on their effectiveness without fully addressing their pedagogical and ethical implications. This creates a need for a more critically informed understanding of how AI influences language learning. This study examines the role of artificial intelligence (AI) in enhancing both academic writing and speaking skills in higher education through a systematic review of recent empirical studies. Drawing on 109 studies published between 2022 and 2025, the review adopts PRISMA guidelines to identify trends in the use of these tools. The findings indicate significant benefits, including increased learner engagement, improved linguistic accuracy, and immediate individualized feedback. These benefits include lexical development, structural coherence, improved pronunciation, and increased learner confidence through iterative practices. However, the review also identifies critical challenges, including risks of overreliance, reduced learner autonomy, and concerns related to linguistic bias. To address these concerns, the study proposes the implementation of the Mediated AI-Pedagogy Cycle, which positions educators as mediating agents between AI affordances and learner development. The study contributes a pedagogically grounded framework for integrating AI into higher education language instruction.

Rewriting the Curriculum: Integrating AI Prompt Engineering into EFL Writing Instruction

Beyond AI-Generated Text: Strengthening Academic Integrity and Critical Thinking in Higher Education

The increasing use of Generative Artificial Intelligence in Higher Education has created new challenges for academic integrity, intellectual authorship, and the development of critical thinking. This study analyzes these challenges and evaluates a pedagogical intervention designed to promote the responsible use of Generative Artificial Intelligence in graduate education. The study was conducted between February 2025 and June 2026 and involved a total of 50 graduate students from three cohorts enrolled in two Master’s programs in Engineering and Business Administration. A qualitative educational action research approach was adopted, based on the analysis of academic assignments, similarity reports, and Artificial Intelligence-assisted writing detection using Turnitin, together with classroom observations and reflective discussions. The pedagogical intervention incorporated strategies based on the UNESCO (2023) guidance, structured prompt design, and the Socratic model. The findings revealed frequent use of Generative Artificial Intelligence-generated content without adequately paraphrasing the generated material, verifying information, or consulting the scientific literature. Following the intervention, students demonstrated greater attention to question formulation, information validation, and the use of reliable academic sources. The study contributes empirical evidence from educational action research showing that structured pedagogical interventions can promote the critical, ethical, and responsible use of Generative Artificial Intelligence in education.

Artificial Intelligence in Academic Writing in Higher Education: A Systematic Literature Review of Pedagogical Integration, Assessment Practices, and Teachers' Perspectives

Artificial intelligence (AI) is rapidly transforming academic writing in higher education by enhancing teaching practices, writing assessment, and student learning. Despite the growing adoption of AI-powered tools such as ChatGPT, Grammarly, PaperPal, and Automated Writing Evaluation (AWE) systems, existing research remains fragmented across pedagogical, assessment, and teacher-related perspectives. This study systematically reviews the current evidence on AI in academic writing using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. Guided by four research questions formulated through the PICo framework, a comprehensive search of Scopus and Web of Science identified 236 records, from which 24 peer-reviewed studies published between 2021 and 2026 met the inclusion criteria following screening, eligibility assessment, and quality appraisal. The findings reveal three dominant themes: (1) AI integration in academic writing teaching and learning, (2) AI-assisted assessment, feedback, and writing evaluation, and (3) teachers' perspectives, ethical issues, and AI adoption. Collectively, the reviewed studies demonstrate that AI enhances writing quality, learner engagement, self-regulated learning, and formative assessment through timely and personalized feedback. However, AI remains limited in evaluating higher-order writing competencies, including critical thinking, originality, and contextual reasoning, reinforcing the continued importance of human expertise in writing assessment. The review further highlights the influence of teachers' perceptions, ethical concerns, and institutional readiness on successful AI implementation. The study contributes a comprehensive synthesis of current research by integrating pedagogical, assessment, and human perspectives through the TPACK, Assessment for Learning, and Technology Acceptance Model frameworks. These findings provide practical implications for educators, institutions, and policymakers while identifying priorities for future research on responsible and pedagogically sound AI integration in academic writing within higher education.

Generative AI in University EFL Writing Instruction: A Systematic Literature Review

Generative artificial intelligence (GenAI), particularly large language model-based tools such as ChatGPT, has rapidly entered university English as a Foreign Language (EFL) writing instruction. These tools can support brainstorming, outlining, drafting, corrective feedback, revision, and academic language refinement. Yet their use also raises concerns about over-reliance, authorship, academic integrity, assessment validity, and the changing role of teachers in writing pedagogy. This systematic literature review synthesizes recent evidence on GenAI in university EFL writing instruction using the PRISMA 2020 framework. Searches were designed for Scopus, Web of Science Core Collection, ERIC, and Education Source/EBSCOhost, covering publications from 1 November 2022 to 22 June 2026. After duplicate removal, title/abstract screening, full-text eligibility assessment, and quality appraisal, 120 studies were included in the qualitative synthesis. Narrative thematic synthesis identified six recurring themes: GenAI as a writing-process scaffold, GenAI-generated feedback, revision uptake and learner engagement, teacher-AI feedback alignment, academic integrity and authorship, and methodological limitations in the existing evidence base. The review concludes that GenAI is most educationally defensible when integrated as a guided formative-feedback resource rather than as a substitute writer or replacement for teacher expertise. Practical implications are offered for assignment design, AI-use disclosure, feedback literacy, prompt literacy, and process-based assessment.