Inteligencia artificial (IA) para la inclusión educativa de estudiantes con discapacidad visual

Autores/as

DOI:

https://doi.org/10.63535/fmbcaq68

Palabras clave:

Inteligencia Artificial, Accesibilidad Educativa, Discapacidad Visual, Inclusión Educativa, Tecnología Asistencial, Formación Docente.

Resumen

La inclusión efectiva de estudiantes con discapacidad visual en el sistema educativo enfrenta barreras significativas, como el acceso a materiales visuales y el desarrollo de habilidades adaptadas. Este proyecto explora la aplicación de herramientas de Inteligencia Artificial (IA) para mejorar la accesibilidad y fomentar una participación equitativa en la educación. Un diagnóstico inicial, basado en encuestas a docentes, reveló una baja familiaridad y uso de tecnologías de apoyo y aplicaciones de IA, a pesar de una alta disposición a participar en iniciativas innovadoras. En respuesta, se seleccionaron y adaptaron herramientas de IA como conversión de texto a voz (TTS), reconocimiento de voz con transcripción automática (ASR) y descripción inteligente de imágenes. Se diseñaron actividades pedagógicas prototipo que integran estas herramientas para facilitar el acceso a información textual y gráfica, promoviendo habilidades como la escucha activa, la expresión oral, el pensamiento crítico y la creatividad. El proyecto también incluye materiales de orientación para educadores y estudiantes sobre la aplicación pedagógica de estas tecnologías. Los resultados preliminares del diseño y la fase diagnóstica indican que la IA tiene un potencial considerable para transformar las prácticas educativas inclusivas, pero resaltan la necesidad de capacitación docente exhaustiva y adaptación contextualizada de las herramientas. Se concluye que es crucial continuar la investigación y el desarrollo de estas soluciones, junto con estrategias de implementación sostenibles y éticamente responsables, para reducir la brecha de accesibilidad educativa.

Descargas

Los datos de descarga aún no están disponibles.

Referencias

Akgul, A. (2022). Accessibility in Online Learning Environments for Students with Visual Impairments: A Systematic Review of the Literature. Journal of Special Education Technology, 37(4), 355-366.

Alghizzawi, M., & Al-Sayyed, R. (2023). The Role of Artificial Intelligence in Enhancing Learning for Students with Visual Impairments. International Journal of Emerging Technologies in Learning (iJET), 18(7), 134-151.

Alhazmi, A. K., & Rahman, A. A. (2022). Artificial Intelligence-Based Image Description Generation for Visually Impaired People: A Review of the Literature. IEEE Access, 10, 87959-87977.

Almerich, G., Suárez-Rodríguez, J., Díaz-García, I., & Orellana, N. (2021). Teacher’s ICT competence: A structural model of the Caren Model. Computers & Education, 167, 104179.

Alshamari, M. (2022). The use of text-to-speech technology to support students with visual impairments in higher education. British Journal of Visual Impairment, 40(3), 443-457.

Basu, S., Kumar, A., & Chakraborty, M. K. (2023). Artificial Intelligence in Education: A Bibliometric Analysis and Future Research Directions. Education and Information Technologies, 28(3), 2679-2710.

Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M. (2012). Defining Twenty-First Century Skills. In P. Griffin, B. McGaw, & E. Care (Eds.), Assessment and Teaching of 21st Century Skills (pp. 17-66). Springer. DOI: https://doi.org/10.1007/978-94-007-2324-5_2

Bond, M., Zawacki-Richter, O., & Bedenlier, S. (2023). Systematic review of research on artificial intelligence applications in higher education – an update. International Journal of Educational Technology in Higher Education, 20(1), 47.

Buhler, C., Kane, S. K., & Ladner, R. E. (2022). Tactile Graphics and Beyond: Accessibility of Visual Information for Blind and Low Vision Individuals. ACM Transactions on Accessible Computing, 15(2), 1-37.

Caballero-Hernández, J. A., López-Vargas, O., & Paredes-Labra, J. (2021). Artificial Intelligence for Inclusive Education: A Systematic Review. Computers & Education, 172, 104254.

Cardona, D. R., Rodríguez-Pérez, C. M., & Salgado-García, A. J. (2023). Ethical Implications of AI in Education for Students with Disabilities: A Systematic Literature Review. Ethics and Information Technology, 25(2), 23.

Carvalho, J. P., Silva, A. M., & Almeida, L. S. (2022). Personalized learning paths with AI for visually impaired students in STEM: A conceptual framework. Journal of STEM Education for Students with Disabilities, 5(1), 34-52.

Ferraro, F. V., Pfeffer, J., & Sutton, R. I. (2023). Scaling Up Excellence: Getting to More Without Settling for Less. Crown Business. (Conceptual, pero relevante para la implementación de innovaciones).

García-Peñalvo, F. J., Corell, A., Abella-García, V., & Grande-de-Prado, M. (2021). Challenges in the Implementation of Artificial Intelligence in Education. Journal of Educational Technology & Society, 24(1), 1-5.

Hidayati, L. N., & Setyaningrum, W. (2023). The Role of Automatic Speech Recognition (ASR) in Supporting Students with Visual Impairments in Collaborative Learning Activities. Journal of Visual Impairment & Blindness, 117(4), 389-401.

Jeong, S. Y., Kim, M., & Lee, J. (2021). Current status and future directions of image captioning for the visually impaired. Sensors, 21(12), 4087.

Khowaja, S. A., & Khuwaja, P. (2023). AI-powered assistive technologies for students with visual impairments: A systematic literature review. Education and Information Technologies, 28(1), 105-143.

Klašnja-Milićević, A., Vesin, B., Ivanović, M., & Budimac, Z. (2021). The Role of AI in Personalized Learning for Students with Disabilities: A Systematic Review. Journal of Educational Computing Research, 59(7), 1359-1391.

Lundqvist, K. O., & Lönn, M. (2021). Text-to-speech technology and its impact on reading comprehension for students with reading difficulties: A systematic review. Scandinavian Journal of Educational Research, 65(5), 791-807.

Mavrou, K., & Kourtis-Kazoullis, V. (2022). Teachers' perceptions and training needs regarding the use of artificial intelligence in inclusive education. International Journal of Inclusive Education, 26(13), 1311-1327.

Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: A guidance for policy-makers. UNESCO.

Moreno-Rodríguez, R., López-Belmonte, J., Pozo-Sánchez, S., & Fuentes-Cabrera, A. (2023). Co-designing AI-based assistive technology with visually impaired users: A case study in higher education. Disability and Rehabilitation: Assistive Technology, 18(7), 835-846.

Naciones Unidas. (2015). Transformar nuestro mundo: la Agenda 2030 para el Desarrollo Sostenible.

Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press.

Okoye, K., Rodriguez-Patarroyo, M., Islam, M. N., & Palade, V. (2024). Systematic review of artificial intelligence in special needs education: Benefits, challenges, and future directions. Journal of Research on Technology in Education, 56(1), 1-23.

Pérez-Marín, D., & Pascual-Nieto, I. (2021). AI and chatbots for improving accessibility and engagement of students with visual disabilities in online learning environments. Universal Access in the Information Society, 20(3), 575-588.

Prime, E. G., Pamment, J. K., & Jones, V. F. (2023). Co-designing Educational Technologies with Teachers: A Systematic Literature Review. Computers & Education, 194, 104695. DOI: https://doi.org/10.1016/j.compedu.2022.104695

Puentedura, R. R. (2014). SAMR: A Contextualized Introduction. [Blog post]. Recuperado de http://hippasus.com/rrpweblog/archives/2014/08/22/SAMRContextualizedIntroduction.pdf

Qazi, A., Alsumait, A., Al-Hunaiyyan, A., & Al-Sharhan, S. (2022). A Systematic Review on the Application of Artificial Intelligence in Education for Students with Visual Impairments. Sustainability, 14(20), 13295.

Rsatbayeva, G., & Nurtayeva, A. (2024). The impact of AI-driven image recognition and description tools on the learning engagement of students with visual impairments. Heliyon, 10(3), e24870.

Santos, J. M., Boticario, J. G., & Pardo, A. (2023). The Role of Explainable AI (XAI) in Building Trust in Assistive Technologies for Visually Impaired Students. Journal of Assistive Technologies, 17(1), 15-28.

Santos, P. L. D., Wahl, S., & Pagnossin, E. (2020). Challenges and opportunities in teaching chemistry to visually impaired students. Journal of Chemical Education, 97(11), 3945-3954.

Scherer, R., Howard, S. K., & Tondeur, J. (2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready? Computers in Human Behavior, 118, 106675. DOI: https://doi.org/10.1016/j.chb.2020.106675

Sharma, R., & Priya, R. (2023). Ethical guidelines for using AI in the education of students with visual impairments. Journal of Information, Communication and Ethics in Society, 21(2), 185-201.

Silva, B. F., Ferreira, M. J., & Bittencourt, I. I. (2022). Developing AI Tutors for Visually Impaired Students: A Human-Centered Approach. IEEE Transactions on Learning Technologies, 15(4), 432-445.

Simpson, C. G., & Mundy, M. A. (2020). Text-to-Speech Technology. In Assistive Technology for Students with Disabilities (pp. 67-84). Routledge.

Soni, A. & K Informed (2023). Enhancing Accessibility through AI: Innovations in Image Description for the Visually Impaired. Journal of AI for Social Good, 2(1), 45-59.

Tzimas, G., & Demetriadis, S. (2021). Artificial Intelligence in Special Education: A Scoping Review. Education Sciences, 11(8), 387.

Vilone, G., & Longo, L. (2021). Explainable Artificial Intelligence: A Systematic Review. ACM Computing Surveys, 54(5), 1-40.

West, J., Darcher, A., & Wright, G. (2022). The use of speech-to-text software for students with learning disabilities: A systematic review. Journal of Special Education Technology, 37(1), 49-60.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2020). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 17(1), 39. DOI: https://doi.org/10.1186/s41239-019-0171-0

Zhang, Y., & Submission, M. P. E. (2022). Automatic speech recognition (ASR) in education: A review of the literature. Educational Technology Research and Development, 70(3), 821-843.

Descargas

Publicado

2025-06-15

Cómo citar

Inteligencia artificial (IA) para la inclusión educativa de estudiantes con discapacidad visual. (2025). Prospherus, 2(2), 738-765. https://doi.org/10.63535/fmbcaq68

Artículos similares

1-10 de 72

También puede Iniciar una búsqueda de similitud avanzada para este artículo.