Artificial Intelligence and Special Education: A Systematic Review of Technologies with an Emphasis on Computer Vision

• Lucas Taylor de Sousa Aires UFC
• Jânio Cayo Borges Lima UFC
• Rubens Fernandes Nunes UFC

DOI: https://doi.org/10.5753/eniac.2025.11784

Abstract

This study presents a Systematic Literature Review (SLR) on the use of assistive technologies based on computer vision with potential for adaptation to inclusive education. The investigation covers publications from 2020 to 2025 and aims to identify solutions designed for people with disabilities and analyze their applicability in educational contexts. Eight studies were analyzed, addressing systems for mobility assistance, visual signal recognition, image description, and assistive communication. The main challenges include technical limitations of devices, a lack of educational adaptations, and insufficient teacher training. Nevertheless, the reviewed works highlight the potential of computer vision to promote autonomy and accessibility, reinforcing the need for future research exploring its direct application in inclusive pedagogical practice.

References

Atiba, S. T., Moses, S. F., Lakoju, M., Semire, F. A., and Aldmour, R. (2020). Machine vision intelligent travel aid for the visually impaired (itavi) in developing countries. In 2020 13th International Conference on Developments in eSystems Engineering (DeSE), pages 317–322. IEEE.

Aydin, A. S., Feiz, S., Ashok, V., and Ramakrishnan, I. (2020). Towards making videos accessible for low vision screen magnifier users. In Proceedings of the 25th international conference on intelligent user interfaces, pages 10–21.

BRASIL (2018). Base Nacional Comum Curricular. Ministério da Educação.

Breiding, P., Kohn, K., and Sturmfels, B. (2024). Computer Vision, pages 163–174. Springer Nature Switzerland, Cham.

Che, C., Zheng, H., Huang, Z., Jiang, W., and Liu, B. (2024). Intelligent robotic control system based on computer vision technology. Applied and Computational Engineering, 64(1):150–155.

de Melo, A. C. C., Souza, E. P. R., and Lima, J. V. V. (2020). A tecnologia assistiva e a inclusão educacional de pessoas com deficiência: um mapeamento sistemático da literatura. Simpósio Brasileiro de Informática na Educação (SBIE), pages 782–791.

de Souza França, J., Paulino, V. C., and do Nascimento, A. S. B. (2022). A tecnologia assistiva como suporte à inclusão da pessoa com deficiência visual no ensino superior: Revisão sistemática. Revincluso-Revista Inclusão & Sociedade, 2(1):29–29.

Fernández-Batanero, J. M., Montenegro-Rueda, M., Fernández-Cerero, J., and 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.

Fernando, S., Ndukwe, C., Virdee, B., and Djemai, R. (2025). Image recognition tools for blind and visually impaired users: An emphasis on the design considerations. ACM Transactions on Accessible Computing, 18(1):1–21.

Galvão, M. C. B. and Ricarte, I. L. M. (2019). Revisão sistemática da literatura: conceituação, produção e publicação. Logeion: Filosofia da informação, 6(1):57–73.

Galvão, T. F. and Pereira, M. G. (2014). Revisões sistemáticas da literatura: passos para sua elaboração. Epidemiologia e serviços de saúde, 23(1):183–184.

Ghosh, A., Mahmud, S. A. A., Uday, T. I. R., and Farid, D. M. (2020). Assistive technology for visually impaired using tensor flow object detection in raspberry pi and coral usb accelerator. In Proceedings of the 2020 IEEE Region 10 Symposium (TENSYMP), pages 186–189. IEEE.

Hamash, M., Khan, M. R., and Tiernan, P. (2025). Inclusive steam education: A framework for teaching cod-2 ing and robotics to students with visually impairment using 3 advanced computer vision. arXiv preprint arXiv:2503.16482.

Hussain, M. (2023). When, where, and which?: Navigating the intersection of computer vision and generative ai for strategic business integration. IEEE Access, 11:127202–127215.

Klann, D., da Rocha Fernandes, A. M., da Silva, E. A., and Parreira, W. D. (2024). Explorando algoritmos de visão computacional em tecnologias assistivas: uma revisão sistemática da literatura. Journal of Health Informatics, 16(Especial).

Krishnan, P., Kattamuri, S., Prabhu, G. R., and Rashmi, M. (2024). Assistive eye: A comparative analysis of yolo object detection models on edge devices. In Proceedings of the 2024 Sixteenth International Conference on Contemporary Computing, pages 104–108.

Luz, J. W. P., Rehfeldt, M. J. H., and Schorr, M. C. (2021). Revisão sistemática da literatura sobre o uso de learning analytics no ensino de programação. Revista Novas Tecnologias na Educação, 19(2):203–212.

Majhi, R. K. and Waoo, A. A. (2024). Advances in computer vision: New horizons and ongoing challenges. ShodhKosh: Journal of Visual and Performing Arts, 5(5):431–438.

Medeiros, M. M. A. and Oliveira, W. W. C. (2024). Special and inclusive education: The role of the school in welcoming students with special needs. Revista Gênero e Interdisciplinaridade, 5(06):117–130.

Nguyen, H., Nguyen, M., Nguyen, Q., Yang, S., and Le, H. (2020). Web-based object detection and sound feedback system for visually impaired people. In 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR), pages 1–6. IEEE.

Nunes, G. S. I., de Barros Filho, E. M., and Coutinho, E. F. (2024). A tecnologia assistiva na inclusão de alunos com deficiência no ambiente escolar: Uma revisão sistemática. In Colloquium Humanarum. ISSN: 1809-8207, volume 21, pages 1–e244872.

Pletsch, M. D. and Mendes, G. M. L. (2024). Cartographies of inclusive education in special education: Scientific production, policies and practices. Revista Brasileira de Educação Especial, 30:e143p.

Prazeres, R. S., Bacchus, J. N., and Pereira, E. C. (2021). Contribuições da tecnologia assistiva para o processo democrático da educação inclusiva. Revista Educação, Pesquisa e Inclusão, 2.

Ribeiro, G. R. d. P. S. and de la Higuera Amato, C. A. (2018). Análise da utilização do desenho universal para aprendizagem. Cadernos de Pós-graduação em Distúrbios do Desenvolvimento, 18(2).

Safiya, K. M. and Pandian, R. (2024). A real-time image captioning framework using computer vision to help the visually impaired. Multimedia Tools and Applications, 83:59413–59438.

Salgado, M. and da Silva, D. J. (2020). Análises de pesquisas sobre a educação especial inclusiva: a (in) diferenciação e o preconceito. Olhar de Professor, 23:1–13.

Santos, S., Rodrigues, B., Graciotto, C., De Almeida, C., Soeiro, J., Amorim, L., Dos Santos, M., and Meroto, M. (2024). Personalizing education: the role of adaptive technologies in individualized education. CONTRIBUCIONES A LAS CIENCIAS SOCIALES, 17(2):01–17.

Sharma, S. (2024). Empowering society through assistive technologies: The role of universities in development and implementation. International Journal of Scientific Research in Engineering and Management.

Tabay, M. D. C. L., Patalingjug, M. J. P., Gesalago, I. A., and Tapales, E. A. (2020). Effective teaching approaches in special education program: A literature review. International Journal of Engineering Research & Technology (IJERT), 9(5):977–981. IJERTV9IS050526.

Trivedi, K. S. (2023). Fundamentals of artificial intelligence. In Microsoft Azure AI Fundamentals Certification Companion: Guide to Prepare for the AI-900 Exam, pages 11–31. Springer.

Varella, K. L. S., Lopes, K. L. C., Vieira, Z. S., da Silva Oliveira, J. C. L., Souza, D. R. O., Polizello, B., de Almeida Polizello, J. W., Barreto, N. P. M., da Rocha, A. P., da Silva Costa, E., et al. (2024). Tecnologias assistivas: Uso de ferramentas tecnológicas para facilitar a inclusão. RCMOS-Revista Científica Multidisciplinar O Saber, 1(2).

ZainEldin, H., Baghdadi, N. A., Gamel, S. A., Aljohani, M., Talaat, F. M., Malki, A., Badawy, M., and Elhosseini, M. (2024). Active convolutional neural networks sign language (activecnn-sl) framework: a paradigm shift in deaf-mute communication. Artificial Intelligence Review, 57(6):162.