ْUsing Artificial Intelligence to Bridge the Gap in Digital Literacy: A Universal Design for Learning Approach
Keywords:
Artificial Intelligence, Universal Design for Learning, Digital Literacy, Accessibility, Inclusive Education, Structural Equation ModelingAbstract
This study explores the integration of Artificial Intelligence (AI) tools within the Universal Design for Learning (UDL) framework to enhance digital literacy and engagement among diverse student populations, particularly those with disabilities. The intervention used Read&Write by Texthelp, providing text-to-speech functionalities and personalized learning pathways to improve accessibility. The study engaged 50 faculty members from international universities and various disciplines in a series of online focus groups. Using a qualitative-to-quantitative approach, focus group data were coded and analyzed through Structural Equation Modeling (SEM) via SmartPLS, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). The analysis revealed strong predictive relationships, with Performance Expectancy (β = 0.62, p < 0.001) and Facilitating Conditions (β = 0.58, p < 0.01) significantly influencing faculty intention to adopt AI-driven UDL. The introduction of AI-enhanced UDL framework positively impacted outcomes, driving a 45% increase in engagement scores and a 23% improvement in digital literacy assessments among students with disabilities. Overall, the intervention resulted in a 52% increase in digital engagement and a 29% boost in digital literacy skills, underscoring the transformative potential of AI-enhanced UDL frameworks. These findings offer a scalable model for promoting inclusivity in education, providing actionable insights for educators and policymakers aiming to bridge digital literacy gaps.
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Gerber, B. L., Guay, D. M., & Burnette, J. (Eds.). (2024). Reaching and teaching students with special needs through art. Taylor & Francis.
Tariq, M. U. (2024). Equity and Inclusion in Learning Ecosystems. In Preparing Students for the Future Educational Paradigm (pp. 155-176). IGI Global.
Edwards, J. (2024). Perceptions and Practices: Exploring How Educators Implement Universal Design for Learning in Higher Education Course Design and Teaching Methods (Doctoral dissertation, Fairleigh Dickinson University).
Sanguinetti, H. (2024). Exploring the Implications: The Impact of Universal Design for Learning on Student Engagement and Motivation in Diverse Classroom Environments.
Craig, S. L., Smith, S. J., & Frey, B. B. (2024). Universal design for learning: connecting teacher implementation to student outcomes. International Journal of Inclusive Education, 28(11), 2458-2474.
Carstairs, M. (2024). Further education teachers adaptation to the introduction of AI in a UDL-empowered environment (Doctoral dissertation, Dublin, National College of Ireland).
Teles, R. O., & Moreira, F. T. (2025). Integrating AI in Formative Assessment Under UDL Principles in Diverse Learning Environments. In Improving Student Assessment With Emerging AI Tools (pp. 95-122). IGI Global Scientific Publishing.
Mrayhi, S., Khribi, M. K., Belhadj, H., & Jemni, M. (2024). Designing future education for all: principles and frameworks. In Envisioning the Future of Education Through Design (pp. 147-177). Singapore: Springer Nature Singapore.
Bhat, M. A., Tiwari, C. K., Bhaskar, P., & Khan, S. T. (2024). Examining ChatGPT adoption among educators in higher educational institutions using extended UTAUT model. Journal of Information, Communication and Ethics in Society, 22(3), 331-353.
Khan, W., Sohail, S., Roomi, M. A., Nisar, Q. A., & Rafiq, M. (2024). Opening a new horizon in digitalization for e-learning in Malaysia: Empirical evidence of Covid-19. Education and Information Technologies, 29(8), 9387-9416.
Alowayr, A. (2022). Determinants of mobile learning adoption: extending the unified theory of acceptance and use of technology (UTAUT). The International Journal of Information and Learning Technology, 39(1), 1-12.
Alowayr, A., & Al-Azawei, A. (2021). Predicting mobile learning acceptance: An integrated model and empirical study based on higher education students' perceptions. Australasian Journal of Educational Technology, 37(3), 38-55.
Mshali, H., & Al-Azawei, A. (2022). Predicting online learning adoption: The role of compatibility, self-efficacy, knowledge sharing, and knowledge acquisition.
Karakoyun, F., & Başaran, B. (2024). Profiling University Students’ Technology Acceptance Through UTAUT. Malaysian Online Journal of Educational Technology, 12(2), 78-92.
Zhu, Z., & Huang, W. (2023). A meta-analysis of mobile learning adoption using extended UTAUT. Information Development, 02666669231176428.
Xue, L., Rashid, A. M., & Ouyang, S. (2024). The Unified Theory of Acceptance and Use of Technology (UTAUT) in Higher Education: A Systematic Review. SAGE Open, 14(1), 21582440241229570.
Qazi, W., Raza, S. A., Khan, K. A., & Salam, J. (2020). Adoption of E-learning system in higher education environments: evidence from modified UTAUT model. J Soc Sci Hum, 7(1), 1-24.
Hyatt, S. E., & Owenz, M. B. (2024). Using Universal Design for Learning and Artificial Intelligence to Support Students with Disabilities. College Teaching, 1-8.
Lohman, L. (2024). Teaching nineteenth-century American history with music: using the possibilities through technology and Universal Design for Learning. American Nineteenth Century History, 1-23.
Kotcherlakota, S., Stamler, L. L., Clark, A., & Howell, M. C. (2024). Implementing universal design for learning in nursing education: Faculty perspectives. Teaching and Learning in Nursing, 19(1), e138-e144.
McKenzie, J., Karisa, A., & Kahonde, C. (2024). Universal Design for Learning in Low- and Middle-Income Countries: A Review of the Literature. International Journal of Disability, Development and Education, 1-19.
Sala-Bars, I., Mumbardó-Adam, C., & Adam-Alcocer, A. L. (2024). Moving towards preservice teachers’ implementation of universal design for learning: the central role of self-efficacy. Teachers and Teaching, 1-19.
De Silva, D., Jayatilleke, S., El-Ayoubi, M., Issadeen, Z., Moraliyage, H., & Mills, N. (2024). The Human-Centred Design of a Universal Module for Artificial Intelligence Literacy in Tertiary Education Institutions. Machine Learning and Knowledge Extraction, 6(2), 1114-1125.
Song, Y., Weisberg, L. R., Zhang, S., Tian, X., Boyer, K. E., & Israel, M. (2024). A framework for inclusive AI learning design for diverse learners. Computers and Education: Artificial Intelligence, 6, 100212. https://doi.org/10.1016/j.caeai.2024.100212.
Almufareh, M. F., Kausar, S., Humayun, M., & Tehsin, S. (2024). A conceptual model for inclusive technology: advancing disability inclusion through artificial intelligence. Journal of Disability Research, 3(1), 20230060.
Bressane, A., Zwirn, D., Essiptchouk, A., Saraiva, A. C. V., de Campos Carvalho, F. L., Formiga, J. K. S., ... & Negri, R. G. (2024). Understanding the role of study strategies and learning disabilities on student academic performance to enhance educational approaches: A proposal using artificial intelligence. Computers and Education: Artificial Intelligence, 6, 100196.
Roski, M., Sebastian, R., Ewerth, R., Hoppe, A., & Nehring, A. (2024). Learning analytics and the Universal Design for Learning (UDL): A clustering approach. Computers & Education, 214, 1050280.
El Naggar, A., Gaad, E., & Inocencio, S. A. M. (2024). Enhancing inclusive education in the UAE: Integrating AI for diverse learning needs. Research in Developmental Disabilities, 147, 104685. https://doi.org/10.1016/j.ridd.2024.104685
Bray, A., Devitt, A., Banks, J., Sanchez Fuentes, S., Sandoval, M., Riviou, K., ... & Terrenzio, S. (2024). What next for Universal Design for Learning? A systematic literature review of technology in UDL implementations at second level. British Journal of Educational Technology, 55(1), 113-138. https://doi.org/10.1111/bjet.13328
Rai, H. L., Saluja, N., & Pimplapure, A. (2024). AI and Learning Disabilities: Ethical and Social Considerations in Educational Technology. Educational Administration: Theory and Practice, 30(5), 12343-12349. https://doi.org/10.53555/kuey.v29i4.5693
Ferreira, R. D. S., & Castro, T. H. C. D. (2024). Participatory and Inclusive Design Models from the Perspective of Universal Design for Children with Autism: A Systematic Review. Education Sciences, 14(6), 613. https://doi.org/10.3390/educsci14060613
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