Gaps, Needs and Expectations: An Inquiry into Students’ Perceptions on the Integration of Generative AI in Supporting Students with Special Learning Needs in Higher Education in Bangladesh

Authors

  • Sayma Arju Stamford University, Bangladesh
  • Jana Chi-san Ho Universidade de São José, Macau/China

DOI:

https://doi.org/10.34630/e-rei.vi.7507

Keywords:

Generative AI, learning disabilities, inclusive education, higher education, Bangladesh, accessibility, student perceptions, AI literacy, adaptive learning, educational technology

Abstract

This study explored how university students with special learning needs (SSLNs) in Bangladesh perceived the integration of generative artificial intelligence (GenAI) as a support mechanism in higher education. Conducted at a private university, the research involved 28 undergraduates who had been formally diagnosed by physicians or psychologists prior to admission. A purposive sampling approach was adopted to ensure participants represented a range of learning disabilities, including dyslexia, ADHD, and mild autism. A mixed-method questionnaire comprising both quantitative and qualitative items was used to gather information on participants’ demographics, experience with GenAI, understanding and evaluation of GenAI, practical applications, perceptions of AI-supported examination processes, ethical considerations, and expectations for AI-assisted learning. Findings revealed that students viewed GenAI as a potential personal tutor, academic coach, and technical assistant that can enhance accessibility, inclusivity, and adaptive learning experiences. Thematic analysis highlighted six key areas of student expectations: personalized and adaptive learning; enhanced feedback and learning support; accessibility and inclusivity; academic skill development; technical and resource support; and student agency through AI literacy and training. During data collection, a researcher was present, and students freely asked questions and shared relevant experiences in a comfortable and pressure-free environment. While the students expressed optimism about GenAI’s capacity to bridge equity and inclusivity gaps, they also emphasized the need for institutional policies that ensured equal access, cultural localization, and ethical use. The study underscores the importance of collaboration between universities, policymakers, and developers to make GenAI a sustainable tool for inclusive higher education in Bangladesh.               

 

References

Al-Azawei, A., Serenelli, F., & Lundqvist, K. (2016). Universal Design for Learning (UDL): A

content analysis of peer-reviewed journal papers from 2012 to 2015. Journal of the Scholarship of

Teaching and Learning, 17(3), 67–81.

Alloway, T. P. (2020). Improving working memory: Supporting students’ learning. Sage

Publications

Alshamy, A., Al-Harthi, A. S. A., & Abdullah, S. (2025). Perceptions of Generative AI Tools in

Higher Education: Insights from Students and Academics at Sultan Qaboos University. Education

Sciences, 15(4), 501. https://doi.org/10.3390/educsci15040501.

Arju, S. & Ho, J.CS. (2026). Towards Inclusive Higher Education: Curriculum Innovation through

Optional Subject Integration for Students with Special Needs. European Scientific Journal. 22(38), 1.

https://doi.org/10.19044/esj.2026.v22n38p1

Business Post. (2023, February 14). Internet costs almost 7 times higher in Bangladesh: Report.

https://businesspostbd.com/news/2023-02-14/internet-costs-almost-7-times-higher-in-bangladesh-report2023-02-14.

Burgstahler, S. (2021). Creating inclusive learning opportunities in higher education: A universal

design toolkit. Harvard Education Press

Courey, S. J., Tappe, P., Siker, J., & LePage, P. (2012). Improved lesson planning with Universal

Design for Learning (UDL). Teacher Education and Special Education, 36(1), 7–27.

Chan, C.K.Y., Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and

challenges in higher education. Int J Educ Technol High Educ 20, (43). https://doi.org/10.1186/s41239-

023-00411-8.

Clarke, V., & Braun, V. (2017). Thematic analysis. The journal of positive psychology, 12(3), 297-

298.

DeVellis, R. F. (2017). Scale development: Theory and applications (4th ed.). SAGE Publications.

Fleming, J., & Haigh, N. (2023). Student authenticity and assessment in the age of AI. Assessment

& Evaluation in Higher Education, 48(5), 709–723.

Farinosi, M., & Melchior, C. (2025). To adopt or to ban? Student perceptions and use of generative

AI in higher education. Humanities and Social Sciences Communications, 12, Article 1684.

https://doi.org/10.1057/s41599-025-05982-7.

Florian, L., & Beaton, M. (2018). Inclusive pedagogy in action: Getting it right for every child.

International Journal of Inclusive Education, 22(8), 870–884.

Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville,

A., & Bengio, Y. (2014). Generative adversarial nets. Advances in Neural Information Processing

Systems, 27, 2672–2680.

Government of the People’s Republic of Bangladesh, Ministry of Education. (2010). National

Education Policy 2010. Secondary and Higher Education Division.

https://planipolis.iiep.unesco.org/sites/default/files/ressources/bangladesh_national_education_policy_2

010.pdf.

Hasib M, Islam MS (2026). Correction: How University students in Bangladesh engage with

ChatGPT: A qualitative study. PLOS ONE 21(3): e0344589.

https://doi.org/10.1371/journal.pone.0344589

Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skills. First

Monday, 7(4). https://doi.org/10.5210/fm.v7i4.942.

Hyatt, S. E., & Owenz, M. B. (2024). Using universal design for learning and artificial intelligence

to support students with disabilities. College Teaching, 1-8.

Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promise and

implications for teaching and learning. Center for Curriculum Redesign

Islam, M. A. (2025). AI in English education: Insights from social science students at the tertiary

level in Bangladesh. http://hdl.handle.net/10361/26825

Julien, G. (2026). The Role of Artificial Intelligence in the Establishment of Inclusive Learning

Environments: A Conceptual Synthesis. Journal of Creative Research in English Literature &

Culture. 2(2).

Larson, B. Z., Moser, C., Caza, A., Muehlfeld, K., & Colombo, L. A. (2024). Critical thinking in

the age of generative AI. Academy of Management Learning & Education, 23(3), 373-378.

Lee, C. C., & Low, M. Y. H. (2024). Using genAI in education: The case for critical thinking.

Frontiers in Artificial Intelligence, 7, 1452131.

Leon, C., Lipuma, J., & Oviedo-Torres, X. (2025, July). Artificial intelligence in STEM education:

A transdisciplinary framework for engagement and innovation. In Frontiers in Education (Vol. 10, p.

1619888). Frontiers.

Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage Publications

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2022). Intelligence unleashed: An

argument for AI in education. Pearson.

Megbowon, F. K. (2025). Generative AI in Higher Education: Perception and

Attitude of Students from a University in South Africa. Studies in Learning and Teaching, 6(2).

https://doi.org/10.46627/silet.v6i2.641.

Mhlanga, D. (2023). Open AI in higher education: Opportunities, challenges, and policy

implications. Education and Information Technologies, 28, 14567–14587.

Nelson, A. S., Santamaría, P. V., Javens, J. S., & Ricaurte, M. (2025). Students’ perceptions of

generative artificial intelligence (GenAI) use in academic writing in English as a foreign language.

Education Sciences, 15(5), 611. https://doi.org/10.3390/educsci15050611.

Pinto, C., Baines, E., & Bakopoulou, I. (2018). The peer relations of pupils with special educational

needs in mainstream primary schools: The importance of meaningful contact and interaction with peers.

British Journal of Educational Psychology, 88(4), 499–519. https://doi.org/10.1111/bjep.12223.

Reid, G., & Peer, L. (2018). Multidisciplinary perspectives on learning disabilities. Routledge.

Rose, D. H., & Dalton, B. (2009). Learning to read in the digital age. Mind, Brain, and Education,

3(2), 74–83.

Saborío-Taylor, S., & Rojas-Ramírez, F. (2024). Universal design for learning and artificial

intelligence in the digital era: Fostering inclusion and autonomous learning. International Journal of

Professional Development, Learners and Learning, 62, ep2408. https://doi.org/10.30935/ijpdll/14694

Selwyn, N. (2022). Education and technology: Key issues and debates (3rd ed.). Bloomsbury

Academic.

Smith, F., & Harvey, L. (2014). Evaluating accessibility in digital learning environments:

Suchanek, P., & Kralova, M. (2025). Generative artificial intelligence expectations and

experiences in management education: ChatGPT use and student satisfaction. Journal of Innovation &

Knowledge, 10(5), Article 100781.

Taber, K. S. (2018). The use of Cronbach's alpha when developing and reporting research

instruments in science education. Research in Science Education, 48(6), 1273–1296.

Tbaishat, D. M., & Elfadel, M. W. (2025). Exploring students’ perceptions of GenAI tools in

higher education: A case study. Cogent Education, 12(1), Article 2560613.

https://doi.org/10.1080/2331186X.2025.2560613DOI:10.1016/j.jik.2025.100781

UNESCO. (2023). Guidance for generative AI in education and research. UNESCO.

https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research.

United Nations. (2006). Convention on the Rights of Persons with Disabilities.

https://www.un.org/development/desa/disabilities/convention-on-the-rights-of-persons-withdisabilities.html.

Wang, X., Lund, B. D., Marengo, A., Pagano, A., Mannuru, N. R., Teel, Z. A., & Parnell, J. A.

(2022). Exploring the potential of generative artificial intelligence models in education: Applications,

challenges, and future directions. Journal of Educational Technology Development and Exchange, 15(1),

1–16. https://doi.org/10.18785/jetde.1501.01

Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI

in education. Learning, Media and Technology, 45(3), 223–235.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of

research on artificial intelligence applications in higher education. International Journal of Educational

Technology in Higher Education, 16(1), 39.

Zhou, J., & Li, F. (2024). Artificial intelligence and the transformation of knowledge creation and

learning: Opportunities and challenges for higher education. Computers & Education: Artificial

Intelligence, 5, 100165. https://doi.org/10.1016/j.caeai.2023.100165.

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Published

2026-07-29

How to Cite

Arju, S., & Ho, J. C.- san. (2026). Gaps, Needs and Expectations: An Inquiry into Students’ Perceptions on the Integration of Generative AI in Supporting Students with Special Learning Needs in Higher Education in Bangladesh. E-Journal of Intercultural Studies. https://doi.org/10.34630/e-rei.vi.7507