The impact of AI-enhanced educational technologies on reading comprehension skills development in students with learning disabilities: Towards individualized future education

Main Article Content

Hind Nasser Almutairi
Abdulaziz Faleh Al-Osail
Mohammed A. Alshehri
Mohammed Ahmed Elhossiny Mohammed
Mashael Nasser Ayed Al-Dosari
Mohamed Ali Nemt-allah
Mohamed Abdellatif

Abstract

This study aimed to examine the effectiveness of AI-enhanced educational technologies compared to conventional instruction methods in improving reading comprehension skills among middle school students with learning disabilities through a quasi-experimental design. Twenty middle school students with identified learning disabilities from the Riyadh region, Saudi Arabia, were randomly assigned to experimental (n=10) or control (n=10) groups. The experimental group participated in an eight-week individualized AI-enhanced reading program featuring adaptive learning algorithms, multi-modal content delivery, and real-time personalized feedback. In contrast, the control group received conventional instruction. A comprehensive 25-item Reading Comprehension Skills Test assessed five domains: literal comprehension, vocabulary in context, inferential comprehension, critical analysis, and application/evaluation. Statistical analysis employed non-parametric procedures, including Mann-Whitney U tests for between-group comparisons and Wilcoxon signed-rank tests for within-group changes. Results demonstrated significant improvements for the experimental group across all reading comprehension domains compared to controls, with the most pronounced effects in critical analysis (p=.004) and total reading comprehension (p=.002). Within-group analysis revealed significant pre-to-post improvements in all domains for the experimental group, with effect sizes indicating substantial gains. Follow-up assessments confirmed sustained improvements without regression, suggesting durable intervention effects. The AI-enhanced platform's personalized, adaptive features effectively addressed the multifaceted nature of reading difficulties in students with learning disabilities, providing evidence for integrating AI technologies in special education interventions to promote individualized learning and long-term academic success.

Downloads

Download data is not yet available.

Article Details

How to Cite
Nasser Almutairi, H., Faleh Al-Osail, A., A. Alshehri, M., Ahmed Elhossiny Mohammed, M., Nasser Ayed Al-Dosari, M., Ali Nemt-allah, M., & Abdellatif, M. (2025). The impact of AI-enhanced educational technologies on reading comprehension skills development in students with learning disabilities: Towards individualized future education. Research Journal in Advanced Humanities, 6(3). https://doi.org/10.58256/03h3er30
Section
Articles

How to Cite

Nasser Almutairi, H., Faleh Al-Osail, A., A. Alshehri, M., Ahmed Elhossiny Mohammed, M., Nasser Ayed Al-Dosari, M., Ali Nemt-allah, M., & Abdellatif, M. (2025). The impact of AI-enhanced educational technologies on reading comprehension skills development in students with learning disabilities: Towards individualized future education. Research Journal in Advanced Humanities, 6(3). https://doi.org/10.58256/03h3er30

Share

References

Adjiovski, B., Bogatinoska, D. C., Ismajloska, M., & Malekian, R. (2024). Enhancing educational technology in lectures for school students with learning disabilities: A comprehensive analysis. SN Computer Science, 5(6), 716. https://doi.org/10.1007/s42979-024-03049-z

Admeur, S., & Attariuas, H. (2024). Personalizing learning Strategies for students failing in school. Contemporary Research Analysis Journal., 01(06), 229-235. https://doi.org/10.55677/craj/09-2024-vol01i6

Akavova, A., Temirkhanova, Z., & Lorsanova, Z. (2023). Adaptive learning and artificial intelligence in the educational space. In E3S Web of Conferences (Vol. 451, Article 06011). 2nd International Conference on Environmental Sustainability Management and Green Technologies (ESMGT 2023). https://doi.org/10.1051/e3sconf/202345106011

Al-Balwi, M., & Muhaidat, M. (2019). The effectiveness of graphic organizers in the development of reading comprehension among students with learning difficulties. Jordanian Journal of Educational Sciences, 17(1), 39–104. https://doi.org/10.47015/17.1.6

Al-Harithi, S. S. (2019). The effectiveness of a program based on mind maps to improve the reading comprehension and attitudes towards reading with students with reading difficulties. Journal of Umm Al-Qura University for Educational & Psychological Sciences, 10(2), 13–57.

Alkhawaldeh, M., Ahmad, M., & Khasawneh, S. (2023). Harnessing the power of artificial intelligence for personalized assistive technology in learning disabilities. Journal of Southwest Jiaotong University, 58(4), 794–805. https://doi.org/10.35741/issn.0258-2724.58.4.60

Almahdawi, A., El-Zeiny, M. E., Aburezeq, I. M., Alqawasmi, A., & Asran, K. M. (2024). Enhancing selective attention of students with learning disabilities through an AI-based strategy. In Proceedings of the 2024 11th International Conference on Social Networks Analysis, Management and Security (SNAMS) (pp. 244–250). IEEE. https://doi.org/10.1109/SNAMS64316.2024.10883808

Alqahtani, K. M. (2018). The effectiveness of a training program in improving the reading comprehension among students with reading disabilities in Al-Baha region. Journal of Educational Sciences, 34, 151–210.

Al-Zahrani, A. B. (2023). The reality of using the Robinson strategy to improve reading comprehension skills among students with learning difficulties and the barriers to its implementation. Assiut University College of Education Journal, 39(3), 127–158. https://doi.org/10.21608/mfes.2023.298553

Al-Saadawi, A. K. (2016). The effectiveness of a program to improve reading comprehension difficulties among a sample of primary school children with learning disabilities (using the mind mapping strategy) [Unpublished doctoral dissertation]. Ain Shams University.

Anderson, J. E., Nguyen, C. A., & Moreira, G. (2025). Generative AI-driven personalization of the community of inquiry model: enhancing individualized learning experiences in digital classrooms. International Journal of Information and Learning Technology, 42(3), 296–310. https://doi.org/10.1108/ijilt-10-2024-0240

Antonis, T. (2022). Learning difficulties and reading comprehension in the first grades of primary school. Open Access Journal of Biogeneric Science and Research, 3(1), 1-5. https://doi.org/10.46718/jbgsr.2022.10.000255

Avdonina, T. B., & Gurieva, D. X. (2020). Innovative methods for teaching children with special needs. Archivarius, 3(48), 46–52. https://doi.org/10.31618/2524-0935-2020-48-3-3

Bañados, M. R. L., Sulfelix, J. N. S., Baste, J. D., Gatus, J. T. C., Van P Rafanan, R., & Cagape, W. E. (2024). Innovative teaching approaches of teachers in teaching students with special needs: A case study. International Journal of Research Publications, 146(1), 360–374. https://doi.org/10.47119/ijrp1001461420246284

Bernacki, M. L., & Walkington, C. (2018). The role of situational interest in personalized learning. Journal of Educational Psychology, 110(6), 864–881. https://doi.org/10.1037/edu0000250

Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068

Bozkurt, A. (2020). Educational technology research patterns in the realm of the digital knowledge age. Journal of Interactive Media in Education, 2020(1), 18. https://doi.org/10.5334/jime.570

Bressane, A., Zwirn, D., Essiptchouk, A., Saraiva, A. C., De Campos Carvalho, F. L., Formiga, J. K., De Castro Medeiros, L. C., & Negri, R. G. (2023). 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. https://doi.org/10.1016/j.caeai.2023.100196

Brunow, D. A., & Cullen, T. A. (2021). Effect of Text-to-Speech and Human Reader on Listening Comprehension for Students with Learning Disabilities. Computers in the Schools, 38(3), 214–231. https://doi.org/10.1080/07380569.2021.1953362

Capin, P., Cho, E., Miciak, J., Roberts, G., & Vaughn, S. (2021). Examining the reading and cognitive profiles of students with significant reading comprehension difficulties. Learning Disability Quarterly, 44(3), 183–196. https://doi.org/10.1177/0731948721989973

Capin, P., Gillam, S. L., Fall, A., Roberts, G., Dille, J. T., & Gillam, R. B. (2022). Understanding the nature and severity of reading difficulties among students with language and reading comprehension difficulties. Annals of Dyslexia, 72(2), 249–275. https://doi.org/10.1007/s11881-022-00255-3

Castro, G. P. B., Chiappe, A., Rodriguez, D. F. B., & Sepulveda, F. G. (2024). Harnessing AI for Education 4.0: Drivers of Personalized Learning. The Electronic Journal of e-Learning, 22(5), 01–14. https://doi.org/10.34190/ejel.22.5.3467

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Cheng, S., & Lai, C. (2019). Facilitating learning for students with special needs: a review of technology-supported special education studies. Journal of Computers in Education, 7(2), 131–153. https://doi.org/10.1007/s40692-019-00150-8

Cummins, J. (2024). How can emerging technologies advance the creation of language-friendly and literacy-friendly schools? Language Culture and Curriculum, 37(1), 106–119. https://doi.org/10.1080/07908318.2024.2306286

Damyanov, P. K. (2024). Effective Pedagogical Strategies and Support Mechanisms for Enhancing the Learning Outcomes of Students with Special Educational Needs: A Systematic Approach. International Journal of Scientific Research and Management (IJSRM), 12(10), 3700–3718. https://doi.org/10.18535/ijsrm/v12i10.el03

Daniel, K., Msambwa, M. M., Antony, F., & Wan, X. (2024). Motivate students for better academic achievement: A systematic review of blended innovative teaching and its impact on learning. Computer Applications in Engineering Education, 32(4), e22733. https://doi.org/10.1002/cae.22733

Deckker, N. D., & Sumanasekara, N. S. (2025). Systematic review on AI in special education: enhancing learning for neurodiverse students. EPRA International Journal of Multidisciplinary Research (IJMR), 11(2), 539–545. https://doi.org/10.36713/epra20360

Dibek, M. I., Kursad, M. S., & Erdogan, T. (2024). Influence of artificial intelligence tools on higher order thinking skills: a meta-analysis. Interactive Learning Environments, 33(3), 2216–2238. https://doi.org/10.1080/10494820.2024.2402028

Dodur, H. M. S., & Ceylan, M. (2025). Academic self‐concept and reading comprehension among students with learning disabilities: Serial mediating effect of reading anxiety and reading motivation. British Journal of Educational Psychology, 95(3), 836–848. https://doi.org/10.1111/bjep.12763

Du Plooy, E., Casteleijn, D., & Franzsen, D. (2024). Personalized adaptive learning in higher education: a scoping review of key characteristics and impact on academic performance and engagement. Heliyon, 10(21), e39630. https://doi.org/10.1016/j.heliyon.2024.e39630

Elleman, A. M., & Oslund, E. L. (2019). Reading Comprehension Research: Implications for Practice and Policy. Policy Insights From the Behavioral and Brain Sciences, 6(1), 3–11. https://doi.org/10.1177/2372732218816339

El-Zeiny, M. E., Alwaely, S. A. K., Faqeeh, M. H., Asran, K. M., & Farhat, D. (2024). AI-based working memory training to reduce reading disabilities in primary students. In Proceedings of the 2024 11th International Conference on Social Networks Analysis, Management and Security (SNAMS) (pp. 74–80). IEEE. https://doi.org/10.1109/SNAMS64316.2024.10883782

Fernández-Batanero, J. M., Montenegro-Rueda, M., Fernández-Cerero, J., & García-Martínez, I. (2022). Assistive technology for the inclusion of students with disabilities: a systematic review. Educational Technology Research and Development, 70(5), 1911–1930. https://doi.org/10.1007/s11423-022-10127-7

Gerlich, M. (2025). AI Tools in Society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006

Giansanti, D., & Pirrera, A. (2025). Integrating AI and Assistive Technologies in Healthcare: Insights from a Narrative Review of Reviews. Healthcare, 13(5), 556. https://doi.org/10.3390/healthcare13050556

Gilmour, A. F., Fuchs, D., & Wehby, J. H. (2018). Are students with disabilities accessing the curriculum? A Meta-Analysis of the reading achievement gap between students with and without Disabilities. Exceptional Children, 85(3), 329–346. https://doi.org/10.1177/0014402918795830

Gligorea, I., Cioca, M., Oancea, R., Gorski, A., Gorski, H., & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature review. Education Sciences, 13(12), 1216. https://doi.org/10.3390/educsci13121216

Guan, C., Mou, J., & Jiang, Z. (2020). Artificial intelligence innovation in education: A twenty-year data-driven historical analysis. International Journal of Innovation Studies, 4(4), 134–147. https://doi.org/10.1016/j.ijis.2020.09.001

Hassan, N. G. (2023). TECHNOLOGY AND THE TRANSFORMATION OF EDUCATIONAL PRACTICES: a FUTURE PERSPECTIVE. International Journal of Economic Business Accounting Agriculture Management and Sharia Administration (IJEBAS), 3(1), 1596–1603. https://doi.org/10.54443/ijebas.v3i1.1136

Hopcan, S., Polat, E., Ozturk, M. E., & Ozturk, L. (2022). Artificial intelligence in special education: a systematic review. Interactive Learning Environments, 31(10), 7335–7353. https://doi.org/10.1080/10494820.2022.2067186

Howard-Gosse, A., Bergey, B. W., & Deacon, S. H. (2023). The reading Challenges, Strategies, and Habits of university students with a history of reading difficulties and their relations to academic achievement. Journal of Learning Disabilities, 57(2), 91–105. https://doi.org/10.1177/00222194231190678

Huang, K., Liu, Y., & Dong, M. (2024). Incorporating AIGC into design ideation: A study on self-efficacy and learning experience acceptance under higher-order thinking. Thinking Skills and Creativity, 52, 101508. https://doi.org/10.1016/j.tsc.2024.101508

Hussein, E., Hussein, M., & Al-Hendawi, M. (2025). Investigation into the Applications of Artificial Intelligence (AI) in Special Education: A Literature Review. Social Sciences, 14(5), 288. https://doi.org/10.3390/socsci14050288

Ishartiwi, I., Handoyo, R. R., Prabawati, W., & Suseno, A. (2023). The individualized instruction application for personal-social skills of students with intellectual disabilities. Jurnal Cakrawala Pendidikan, 42(2), 280-294. https://doi.org/10.21831/cp.v42i2.49240

James, E., Thompson, P. A., Bowes, L., & Nation, K. (2024). What are the long-term prospects for children with comprehension weaknesses? A registered report investigating education and employment outcomes. Journal of Educational Psychology, 116(6), 1019–1033. https://doi.org/10.1037/edu0000898

Joseph, L., Ross, K., Xia, Q., Amspaugh, L. A., & Accurso, J. (2021). Reading Comprehension Instruction for Students with Intellectual Disabilities: A Systematic Literature Review. International Journal of Disability Development and Education, 70(3), 314–339. https://doi.org/10.1080/1034912x.2021.1892033

Kamalov, F., Calonge, D. S., & Gurrib, I. (2023). New era of Artificial intelligence in Education: Towards a sustainable Multifaceted Revolution. Sustainability, 15(16), 12451. https://doi.org/10.3390/su151612451

Kampylafka, C., Polychroni, F., & Antoniou, A. (2023). Primary School Students with Reading Comprehension Difficulties and Students with Learning Disabilities: Exploring Their Goal Orientations, Classroom Goal Structures, and Self-Regulated Learning Strategies. Behavioral Sciences, 13(2), 78. https://doi.org/10.3390/bs13020078

Katiyar, P., Awasthi, V., Pratap, R., Mishra, K., Shukla, N., Singh, R., & Tiwari, M. (2024). AI-driven personalized learning systems: enhancing educational effectiveness. Educational Administration Theory and Practices, 30(5), 11514-11524. https://doi.org/10.53555/kuey.v30i5.4961

Kendeou, P., McMaster, K. L., & Christ, T. J. (2016). Reading comprehension. Policy Insights From the Behavioral and Brain Sciences, 3(1), 62–69. https://doi.org/10.1177/2372732215624707

Kim, S. J., & Lee, E. J. (2025). A study on the application of individualized instruction to improve computational skills of students at risk for mathematics learning disabilities. Korean Journal of Special Education, 59(4), 161–192. https://doi.org/10.15861/kjse.2025.59.4.161

Kocaj, A., Cortina, K. S., Vereb, A. F., & Carlisle, J. F. (2023). Exploring individual changes in disability status and their relations to reading comprehension development. Remedial and Special Education, 46(1), 3–17. https://doi.org/10.1177/07419325231217521

Lazarus, K. U., & Anwalimhobor, N. B. I. (2023). Metacognitive Awareness of Reading Strategies as Predictors of Reading Comprehension Achievement among Students with Learning Disabilities in Nigeria. IJDS Indonesian Journal of Disability Studies, 10(1), 83-94. https://doi.org/10.21776/ub.ijds.2023.010.01.07

Lewis, R. B., & Lewis, R. B. (1998). Assistive technology and learning disabilities. Journal of Learning Disabilities, 31(1), 16–26. https://doi.org/10.1177/002221949803100103

Liu, M., Zhang, J., Nyagoga, L. M., & Liu, L. (2023). Student-AI Question Cocreation for Enhancing reading Comprehension. IEEE Transactions on Learning Technologies, 17, 815–826. https://doi.org/10.1109/tlt.2023.3333439

Liu, W., & Wang, Y. (2024). The effects of using AI tools on critical thinking in English literature classes among EFL learners: an intervention study. European Journal of Education, 59(4), e12804. https://doi.org/10.1111/ejed.12804

Lu, J., Zheng, R., Gong, Z., & Xu, H. (2024). Supporting Teachers’ professional Development with Generative AI: The Effects on Higher Order Thinking and Self-Efficacy. IEEE Transactions on Learning Technologies, 17, 1279–1289. https://doi.org/10.1109/tlt.2024.3369690

Luckin, R., & Cukurova, M. (2019). Designing educational technologies in the age of AI: A learning sciences‐driven approach. British Journal of Educational Technology, 50(6), 2824–2838. https://doi.org/10.1111/bjet.12861

Maghsudi, S., Lan, A., Xu, J., & van der Schaar, M. (2021). Personalized education in the artificial intelligence era: What to expect next. IEEE Signal Processing Magazine, 38(3), 37–50. https://doi.org/10.1109/MSP.2021.3055032

McKenna, J. W., Shin, M., & Ciullo, S. (2015). Evaluating reading and mathematics instruction for students with learning disabilities. Learning Disability Quarterly, 38(4), 195–207. https://doi.org/10.1177/0731948714564576

Murtaza, M., Ahmed, Y., Shamsi, J. A., Sherwani, F., & Usman, M. (2022). AI-based personalized e-learning systems: Issues, challenges, and solutions. IEEE Access, 10, 81323–81342. https://doi.org/10.1109/ACCESS.2022.3193938

Murtaza, M., Ahmed, Y., Shamsi, J., Sherwani, F., & Usman, M. (2022). AI-based personalized e-learning systems: Issues, challenges, and solutions. IEEE Access, 10, 81323–81342. https://doi.org/10.1109/ACCESS.2022.3193938

Nation, K. (2019). Children’s reading difficulties, language, and reflections on the simple view of reading. Australian Journal of Learning Difficulties, 24(1), 47–73. https://doi.org/10.1080/19404158.2019.1609272

Naz, F., & Murad, H. S. (2017). Innovative teaching has a positive impact on the performance of diverse students. SAGE Open, 7(4), 1–8. https://doi.org/10.1177/2158244017734022

Papalexandratou, N. P., Stathopoulou, N. A., & Skanavis, C. (2024). The use of artificial intelligence in the education of students with learning disabilities. Global Journal of Engineering and Technology Advances, 21(3), 033–049. https://doi.org/10.30574/gjeta.2024.21.3.0223

Perelmutter, B., McGregor, K. K., & Gordon, K. R. (2017). Assistive technology interventions for adolescents and adults with learning disabilities: An evidence-based systematic review and meta-analysis. Computers & Education, 114, 139–163. https://doi.org/10.1016/j.compedu.2017.06.005

Pesovski, I., Santos, R., Henriques, R., & Trajkovik, V. (2024). Generative AI for customizable learning experiences. Sustainability, 16(7), 3034. https://doi.org/10.3390/su16073034

Peterson, R. L., McGrath, L. M., Willcutt, E. G., Keenan, J. M., Olson, R. K., & Pennington, B. F. (2021). How specific are learning disabilities? Journal of Learning Disabilities, 54(6), 466–483. https://doi.org/10.1177/0022219420982981

Quinn, J. M., Wagner, R. K., Petscher, Y., Roberts, G., Menzel, A. J., & Schatschneider, C. (2020). Differential codevelopment of vocabulary knowledge and reading comprehension for students with and without learning disabilities. Journal of Educational Psychology, 112(3), 608–627. https://doi.org/10.1037/edu0000382

Rad, H. S. (2025). Reinforcing L2 reading comprehension through artificial intelligence intervention: refining engagement to foster self-regulated learning. Smart Learning Environments, 12(1), 23. https://doi.org/10.1186/s40561-025-00377-2

Rane, N., Choudhary, S., & Rane, J. (2023). Education 4.0 and 5.0: Integrating Artificial Intelligence (AI) for personalized and adaptive learning. SSRN Electronic Journal, 1(1), 29–43. https://doi.org/10.2139/ssrn.4638365

Redhu, V., Singh, A. K., & Saravanan, M. (2024). AI-enhanced learning assistant platform: An advanced system for Q&A generation from provided content, answer evaluation, identification of students’ weak areas, recursive testing for strengthening knowledge, integrated query forum, and expert chat support. In Proceedings of the 2024 2nd International Conference on Artificial Intelligence and Machine Learning Applications (AIMLA): Theme—Healthcare and Internet of Things (pp. 1–6). IEEE. https://doi.org/10.1109/AIMLA59606.2024.10531533

Rodríguez-Cano, S., Cuesta-Gómez, J. L., Delgado-Benito, V., & De La Fuente-Anuncibay, R. (2022). Educational Technology as a Support Tool for Students with Specific Learning Difficulties—Future Education Professionals’ Perspective. Sustainability, 14(10), 6177. https://doi.org/10.3390/su14106177

Sarisahin, S. (2020). Reading Comprehension Strategies for students with learning disabilities who are emergent bilingual. Intervention in School and Clinic, 56(1), 3–12. https://doi.org/10.1177/1053451220910731

Schulte, A. C., Stevens, J. J., Elliott, S. N., Tindal, G., & Nese, J. F. T. (2016). Achievement gaps for students with disabilities: Stable, widening, or narrowing on a state-wide reading comprehension test? Journal of Educational Psychology, 108(7), 925–942. https://doi.org/10.1037/edu0000107

Shanahan, E., Choi, S., An, J., Casey-Wilke, B., Birinci, S., Roberts, C., & Reno, E. (2024). Ongoing teacher Support for Data-Based Individualization: a Meta-Analysis and Synthesis. Journal of Learning Disabilities, 58(1), 3-18. https://doi.org/10.1177/00222194241271335

Shemshack, A., & Spector, J. M. (2020). A systematic literature review of personalized learning terms. Smart Learning Environments, 7(1), 33. https://doi.org/10.1186/s40561-020-00140-9

Söğüt, D. A., & Melekoğlu, M. A. (2025). Effect of the Self-Determination Learning Model of instruction on reading comprehension and Self-Determination skills of students with learning disabilities. Learning Disability Quarterly, 48(2), 130–142. https://doi.org/10.1177/07319487241301054

Sokpheng, S., & Meng, L. H. (2022). Comparison of Modern and Conventional Learning Methods for Children with Special Needs. Journal of Asian Multicultural Research for Educational Study, 3(1), 14–22. https://doi.org/10.47616/jamres.v3i1.264

Süer, S., Kumaş, Ö. A., & Karagül, A. (2021). Investigating the Teachers’ Innovative Pedagogical Practices towards Students with Special Needs. Academia Eğitim Araştırmaları Dergisi, 6(2), 363–381. https://doi.org/10.53506/egitim.902289

Sumanth, N. S., Priya, S. V., & KS., K. (2024). AI-enhanced learning assistant platform. In Proceedings of the 2024 International Conference on Inventive Computation Technologies (ICICT) (pp. 846–852). IEEE. https://doi.org/10.1109/ICICT60155.2024.10545011

Sumanth, N. S., Priya, S. V., M, S., & K.S., K. (2024). AI-enhanced learning assistant platform. In Proceedings of the 2024 International Conference on Inventive Computation Technologies (ICICT) (pp. 846–852). IEEE. https://doi.org/10.1109/ICICT60155.2024.10545011

Svensson, I., Nordström, T., Lindeblad, E., Gustafson, S., Björn, M., Sand, C., Almgren/Bäck, G., & Nilsson, S. (2019). Effects of assistive technology for students with reading and writing disabilities. Disability and Rehabilitation Assistive Technology, 16(2), 196–208. https://doi.org/10.1080/17483107.2019.1646821

Talbott, E., Lloyd, J. W., & Tankersley, M. (1994). Effects of Reading Comprehension Interventions for Students with Learning Disabilities. Learning Disability Quarterly, 17(3), 223–232. https://doi.org/10.2307/1511075

Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial Intelligence in Education: AIED for Personalised Learning Pathways. The Electronic Journal of e-Learning, 20(5), 639–653. https://doi.org/10.34190/ejel.20.5.2597

Taşkın, M. (2025). Artificial Intelligence in Personalized Education: Enhancing learning outcomes through adaptive technologies and Data-Driven Insights. Human Computer Interaction., 8(1), 173. https://doi.org/10.62802/ygye0506

Torppa, M., Vasalampi, K., Eklund, K., Sulkunen, S., & Niemi, P. (2019). Reading comprehension difficulty is often distinct from difficulty in reading fluency and accompanied with problems in motivation and school well-being. Educational Psychology, 40(1), 62–81. https://doi.org/10.1080/01443410.2019.1670334

Valtonen, T., López-Pernas, S., Saqr, M., Vartiainen, H., Sointu, E. T., & Tedre, M. (2021). The nature and building blocks of educational technology research. Computers in Human Behavior, 128, 107123. https://doi.org/10.1016/j.chb.2021.107123

Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1), 15. https://doi.org/10.1186/s41239-024-00448-3

Wang, C., Chen, X., Yu, T., Liu, Y., & Jing, Y. (2024). Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanities and Social Sciences Communications, 11(1), 256. https://doi.org/10.1057/s41599-024-02717-y

Wang, S., Sun, Z., & Chen, Y. (2022). Effects of higher education institutes’ artificial intelligence capability on students’ self-efficacy, creativity and learning performance. Education and Information Technologies, 28(5), 4919–4939. https://doi.org/10.1007/s10639-022-11338-4

Willcutt, E. G., McGrath, L. M., Pennington, B. F., Keenan, J. M., DeFries, J. C., Olson, R. K., & Wadsworth, S. J. (2019). Understanding comorbidity between specific learning disabilities. New Directions for Child and Adolescent Development, 2019(165), 91–109. https://doi.org/10.1002/cad.20291

Wu, X. (2024). Artificial Intelligence in L2 learning: A meta-analysis of contextual, instructional, and social-emotional moderators. System, 126, 103498. https://doi.org/10.1016/j.system.2024.103498

Xu, W., & Ouyang, F. (2021). A systematic review of AI role in the educational system based on a proposed conceptual framework. Education and Information Technologies, 27(3), 4195–4223. https://doi.org/10.1007/s10639-021-10774-y

Yang, H. (2022). Effect of Story Structure Instruction based on Visual Analysis on reading Comprehension intervention for Dyslexic students. Computational Intelligence and Neuroscience, 2022(1), 9479709. https://doi.org/10.1155/2022/9479709

Yang, Y., Chen, L., He, W., Sun, D., & Salas-Pilco, S. Z. (2024). Artificial Intelligence for Enhancing Special Education for K-12: A Decade of Trends, Themes, and Global Insights (2013–2023). International Journal of Artificial Intelligence in Education. 1–49. https://doi.org/10.1007/s40593-024-00422-0

Younas, M., El-Dakhs, D. A. S., & Jiang, Y. (2025). A comprehensive systematic review of AI-driven approaches to self-directed learning. IEEE Access, 13, 38387–38403. https://doi.org/10.1109/ACCESS.2025.3546319

Yu, H., Miao, C., Leung, C., & White, T. J. (2017). Towards AI-powered personalization in MOOC learning. Npj Science of Learning, 2(1), 17. https://doi.org/10.1038/s41539-017-0016-3

Zdravkova, K., Krasniqi, V., Dalipi, F., & Ferati, M. (2022). Cutting-edge communication and learning assistive technologies for disabled children: An artificial intelligence perspective. Frontiers in Artificial Intelligence, 5, 970430. https://doi.org/10.3389/frai.2022.970430

Zhang, J., Zou, L., Miao, J., Zhang, Y., Hwang, G., & Zhu, Y. (2019). An individualized intervention approach to improving university students’ learning performance and interactive behaviors in a blended learning environment. Interactive Learning Environments, 28(2), 231–245. https://doi.org/10.1080/10494820.2019.1636078

Zhang, L., Carter, R. A., Liu, Y., & Peng, P. (2024). Let’s CHAT about artificial intelligence for students with disabilities: A systematic literature review and meta-analysis. Review of Educational Research, 20(10), 1–43. https://doi.org/10.3102/00346543241293424