Exploring the Potential of Artificial Intelligence in Supporting Dyslexic ESL Learners in Higher Education: A Theoretical Perspective

Authors

  • Fawzi Alghazali

    College of Arts & Languages, Mohamed Bin Zayed University for Humanities, Abu Dhabi 106621, United Arab Emirates
  • Edward Hogshire

    College of Arts & Languages, Mohamed Bin Zayed University for Humanities, Abu Dhabi 106621, United Arab Emirates
  • Hanene Lahiani

    College of Education, English Language and Translation Program, Al Ain University, Abu Dhabi 64141, United Arab Emirates
  • Ahmad M. Al Mahamed

    College of Arts, Education and Social Sciences, Abu Dhabi University, Abu Dhabi 59911, United Arab Emirates
  • Mohamad Abou Adel

    College of Education, Arabic Language and Literature Program, Al Ain University, Abu Dhabi 64141, United Arab Emirates

DOI:

https://doi.org/10.30564/fls.v7i11.9532
Received: 15 April 2025 | Revised: 23 April 2025 | Accepted: 1 September 2025 | Published Online: 22 October 2025

Abstract

This paper examines how AI can transform the delivery of learning to dyslexic learners of English as a Second Language (ESL), specifically within higher education. It explores how dyslexia impedes the acquisition of a second language, particularly in relation to reading, comprehension, and writing. AI tools are opening new avenues that provide exciting opportunities for tackling these challenges, through personalized adaptive learning experiences that respond to each learner's differing needs. The paper employs a comprehensive survey of the literature on dyslexia, language learning, and AI in education, to identify key gaps in dyslexic learners support. AI-based tools, such as speech recognition, NLP and adaptive learning platforms, are also assessed in terms of optimizing ESL learning for dyslexic students. It also discusses some case studies where AI-based tools have been successfully integrated in ESL classroom. The study reveals that even though AI enhances learning and student engagement, it raises privacy, infrastructure and educator readiness issues. It concludes with strategic recommendations and advocates for a collaborative approach involving educators, technology  This paper examines how AI can transform the delivery of learning to dyslexic learners of English as a Second Language (ESL), specifically within higher education. It explores how dyslexia impedes the acquisition of a second language, particularly in relation to reading, comprehension, and writing. AI tools are opening new avenues that provide exciting opportunities for tackling these challenges, through personalized adaptive learning experiences that respond to each learner's differing needs. The paper employs a comprehensive survey of the literature on dyslexia, language learning, and AI in education, to identify key gaps in dyslexic learners support. AI-based tools, such as speech recognition, NLP and adaptive learning platforms, are also assessed in terms of optimizing ESL learning for dyslexic students. It also discusses some case studies where AI-based tools have been successfully integrated in ESL classroom. The study reveals that even though AI enhances learning and student engagement, it raises privacy, infrastructure and educator readiness issues. It concludes with strategic recommendations and advocates for a collaborative approach involving educators, technology developers, and policymakers to harness AI's full potential in supporting dyslexic ESL learners, thereby promoting equitable access to educational opportunities.

Keywords:

Dyslexia; Language Acquisition; AI in Education; Artificial Intelligence; Natural Language Processing

References

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How to Cite

Alghazali, F., Hogshire, E., Lahiani, H., Al Mahamed, A. M., & Abou Adel, M. (2025). Exploring the Potential of Artificial Intelligence in Supporting Dyslexic ESL Learners in Higher Education: A Theoretical Perspective. Forum for Linguistic Studies, 7(11), 773–784. https://doi.org/10.30564/fls.v7i11.9532

Issue

Vol. 7 , Iss. 11 (November 2025): In progress

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Article

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Copyright © 2025 Fawzi Alghazali, Edward Hogshire, Hanene Lahiani, Ahmad M. Al Mahamed, Mohamad Abou Adel

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This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.