Citation

Shahzad, Waheed and Abbas, Furrakh (2026) Automated Evaluation of ESL Learners’ English Writing Skills in English-Medium Instruction (EMI) through AI Writing Analytics. Journal of Communication, Language and Culture, 6 (1). pp. 147-166. ISSN 2805-444X

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Abstract

This study analyses the use of artificial intelligence (AI)-driven automated writing evaluation (AWE) analytics and examines their role in enhancing the English writing skills of ESL learners in English-medium instruction (EMI) contexts. The review synthesises contemporary AWE systems, including those based on deep learning (DL), natural language processing (NLP), and generative AI approaches. It provides a detailed discussion of methods used for real-time feedback delivery, linguistic feature extraction, and the integration of AI-driven assessment with traditional teacher and peer feedback practices. In addition, the study critically evaluates empirical findings that highlight both the benefits and limitations of AI writing analytics in higher education EMI settings, including pedagogical, technical, and ethical challenges. Finally, the paper identifies future research directions and underscores the need for hybrid evaluation models that combine human oversight with automated systems to support technical accuracy, systematic assessment, and the development of higher-order writing skills in EMI contexts.

Item Type:	Article
Uncontrolled Keywords:	AI writing analytics, automated writing evaluation, automated essay scoring, generative AI, English-medium instruction (EMI), ESL/EFL, feedback, formative assessment
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions:	Others
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	08 Jul 2026 05:14
Last Modified:	08 Jul 2026 05:14
URII:	http://shdl.mmu.edu.my/id/eprint/16239

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