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AI-Assisted Feedback, Learner Engagement, and ESL Writing Development among Malaysian University Students: A Conceptual Framework

2026 · International journal of research and innovation in social science · 0 citations

Abstract

The emergence of an increasing number of writing assistance tools using artificial intelligence (AI) has transformed feedback provision, text revision, and academic writing practice by university students. In the context of English as a Second Language (ESL), AI-assisted writing tools might assist in grammatical correction, vocabulary selection, sentence construction, idea formation, and writing. However, the pedagogical value of AI-assisted writing cannot be taken for granted based on the availability of the tool alone. Existing literature has focused on issues regarding learners' perception towards the tool, its efficacy, or the writing outcome. Yet, there is less conceptual discussion that explains the development of writing skills through the mediation of learners' engagement and feedback interaction via AI-assisted writing. This conceptual paper aims to provide a theoretically informed conceptual framework that could facilitate the development of ESL writing skills via AI-assisted writing among Malaysian university students through Sociocultural Theory, Technology-Enhanced Language Learning (TELL) theory, learner engagement theory, and written corrective feedback literature. The framework argues that AI tools can contribute to ESL writing development only when students actively notice, evaluate and apply feedback in ways that promote self-regulation and writing autonomy. Given its conceptual nature, this paper does not claim empirical validation; instead, it offers theoretically informed propositions for future mixed-methods and longitudinal research. The paper contributes to TESL scholarship by integrating technological affordances with learner-centred and context-sensitive pedagogical processes in Malaysian higher education.

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