Aksesibilitas Peserta Didik Tunanetra Dalam Pembelajaran Berbasis Kecerdasan Artifisial: Kerangka Lima Lapis Hasil Analisis Dokumen
DOI:
https://doi.org/10.59944/jipsi.v5i4.1799Keywords:
accessibility, students with visual impairments, artificial intelligence, assistive technologyAbstract
Artificial intelligence creates opportunities for students with visual impairments to access learning materials in adaptable formats, obtain descriptions of visual information, and receive support that responds to their pace of interaction. The availability of an application, however, does not constitute accessibility. This study analyses the dimensions of accessibility, the barriers that emerge, and the conditions required for meaningful participation in such learning. A qualitative descriptive approach was employed through thematic document analysis of 23 sources, comprising 19 scholarly articles published between 2022 and 2026 and four policy or accessibility-standard documents. The analysis yields a five-layer framework: operability; informational equivalence and modality flexibility; output reliability and verifiability; user competence and pedagogical mediation; and governance and infrastructure. Artificial intelligence can strengthen learning independence, yet it also generates new barriers: unlabeled controls, loss of meaning in visual materials, inaccurate outputs, bias, privacy risks, and unequal access to devices. The framework is offered as an initial audit reference requiring field validation.
References
Adnin, R., & Das, M. (2024). “I look at it as the king of knowledge”: How blind people use and understand generative AI tools. In Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’24) (Article 64, pp. 1–14). Association for Computing Machinery. https://doi.org/10.1145/3663548.3675631
Bahadır, E., & Bahadır, Z. (2024). Information of difficulties faced by visually impaired students in the learning process at school. Trends in Computer Science and Information Technology, 9(3), 81–89. https://doi.org/10.17352/tcsit.000085
Barak Ventura, R., Hamilton-Fletcher, G., & Rizzo, J.-R. (2026). From abandonment to adoption: Advancing assistive technologies for blindness and low vision in the AI era. Frontiers in Digital Health, Article 1719746. https://doi.org/10.3389/fdgth.2025.1719746
Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., & Shawe-Taylor, J. (2024). Artificial intelligence alone will not democratise education: On educational inequality, techno-solutionism and inclusive tools. Sustainability, 16(2), Article 781. https://doi.org/10.3390/su16020781
Dumitru, C., Abdulsahib, G. M., Khalaf, O. I., & Bennour, A. (2026). Integrating artificial intelligence in supporting students with disabilities in higher education: An integrative review. Technology and Disability, 38(1), 3–24. https://doi.org/10.1177/10554181251355428
El Morr, C., Kundi, B., Mobeen, F., Taleghani, S., El-Lahib, Y., & Gorman, R. (2024). AI and disability: A systematic scoping review. Health Informatics Journal, 30. https://doi.org/10.1177/14604582241285743
Gadekallu, T. R., Yenduri, G., Kaluri, R., Rajput, D. S., Lakshmanna, K., Fang, K., Chen, J., & Wang, W. (2025). The role of GPT in promoting inclusive higher education for people with various learning disabilities: A review. PeerJ Computer Science, 11, Article e2400. https://doi.org/10.7717/peerj-cs.2400
Hanan, A., Marjani, G. I., Suherman, U., Firdaus, A., Albustomi, A. G., Goffary, I., Anwar, S., & Arken, M. R. (2023). Harnessing Technology for Environmental Method: Cultivating High Order Thinking Skills for Sustainable Maritime Development Knowledge. IOP Conference Series: Earth and Environmental Science, 1265(1), 12004. https://doi.org/10.1088/1755-1315/1265/1/012004
Khlaif, Z. N., Alshakhshir, R., Hamamra, B. M. T., & Joma, A. (2026). Assistive generative AI for visually impaired learners: Personalization and inclusion in higher education. International Journal of Artificial Intelligence in Education, 36(1–2), Article 100008. https://doi.org/10.1016/j.ijaied.2026.100008
Kurniawan, S. B., Umar, F., Mustaqimah, U., Cahyani, L. A., & Yusuf, M. (2025). Evaluasi aksesibilitas sarana dan prasarana kampus bagi mahasiswa penyandang disabilitas di Universitas Sebelas Maret. Jurnal Ortopedagogia, 11(2), 423–427. https://doi.org/10.17977/um031v11i22025p423-427
Leporini, B., Buzzi, M., & Della Penna, G. (2025). A preliminary evaluation of generative AI tools for blind users: Usability and screen reader interaction. In Proceedings of the 18th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA ’25) (pp. 562–568). Association for Computing Machinery. https://doi.org/10.1145/3733155.3737910
Mina, P. N. R., Solon, I. M., Sanchez, F. R., Delante, T. K., Villegas, J. K., Basay, F. J., Andales, J., Pasko, F., Estrera, M. F. R., Samson, R., Jr., & Mutya, R. (2023). Leveraging education through artificial intelligence virtual assistance: A case study of visually impaired learners. International Journal of Educational Innovation and Research, 2(1), 10–22. https://doi.org/10.31949/ijeir.v2i1.3001
Niu, L., Manohar, A., Ning, W., & Dong, H. (2026). Understanding stigma through camera-based mobile apps: Studies on visually impaired users. CoDesign, 1–23. https://doi.org/10.1080/15710882.2025.2610363
Perera, M., Ananthanarayan, S., Goncu, C., & Marriott, K. (2025). The sky is the limit: Understanding how generative AI can enhance screen reader users’ experience with productivity applications. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25) (Article 1165, pp. 1–17). Association for Computing Machinery. https://doi.org/10.1145/3706598.3713634
Pieriboni, G., Buzzi, M., & Leporini, B. (2026). STEM education and ICT-enhanced tools for students with disabilities: A five-year review. Universal Access in the Information Society, 25(1), Article 3. https://doi.org/10.1007/s10209-025-01282-8
Republik Indonesia. (2016). Undang-Undang Republik Indonesia Nomor 8 Tahun 2016 tentang Penyandang Disabilitas. Lembaran Negara Republik Indonesia Tahun 2016 Nomor 69.
Riyanti, R., Sauri, R. S., & Anwar, S. (2026). Transformation of Student Management in Increasing Student Participation in Non Academic Activities. At Turots: Jurnal Pendidikan Islam, 8(1), 309–319. https://doi.org/https://doi.org/10.51468/jpi.v8i1.1131
Said, M., Hn, W., Azizah, S., Darmawan, D., & Anwar, C. R. (2022). Digital skills of blind college students in the educational process during a pandemic. Journal of ICSAR, 6(1), 67–77. https://doi.org/10.17977/um005v6i12022p067
Sharma, T., Tseng, Y.-Y., Zhang, L., Ide, A., Mack, K. A., Findlater, L., Gurari, D., & Wang, Y. (2025). “Before, I asked my mom, now I ask ChatGPT”: Visual privacy management with generative AI for blind and low-vision people. In Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’25) (Article 17). Association for Computing Machinery. https://doi.org/10.1145/3663547.3746335
Suherman, U., Cipta, E. S., Anwar, S., Kadir, W. A., Fakhrurrozi, M. F., Namira, S. H., & Halimatussadiyah, W. (2025). Implementing a Kindness-Based Leadership Strategy in Islamic Elementary Education. EDUKASIA: Jurnal Pendidikan Dan Pembelajaran, 6(1), 281–292. https://doi.org/https://doi.org/10.62775/edukasia.v6i1.1384
Tang, X., Abdolrahmani, A., Gergle, D., & Piper, A. M. (2025). Everyday uncertainty: How blind people use GenAI tools for information access. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25) (pp. 1–17). Association for Computing Machinery. https://doi.org/10.1145/3706598.3713433
United Nations Educational, Scientific and Cultural Organization. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Vader, M.-L. P., Baguhn, S. J., & Silverman, A. M. (2025). Emerging trends in artificial intelligence and blindness: A Delphi study. Journal of Visual Impairment & Blindness, 119(6), 495–506. https://doi.org/10.1177/0145482X251399194
Voultsiou, E., & Moussiades, L. (2025). A systematic review of AI, VR, and LLM applications in special education: Opportunities, challenges, and future directions. Education and Information Technologies, 30(13), 19141–19181. https://doi.org/10.1007/s10639-025-13550-4
World Wide Web Consortium. (2024). Web Content Accessibility Guidelines (WCAG) 2.2. https://www.w3.org/TR/WCAG22/
World Wide Web Consortium. (2025). Guidance on applying WCAG 2 to non-web information and communications technologies (WCAG2ICT) 2.2. https://www.w3.org/TR/wcag2ict-22/
