Ética e inteligencia artificial en entornos educativos rurales: percepciones, prácticas y brechas regulatorias en una institución colombiana

Autores/as

DOI:

https://doi.org/10.70577/s.e.v4i3.130

Palabras clave:

clave: ética de la inteligencia artificial, educación rural, formación docente, privacidad de datos, integridad académica, regulación educativa, Colombia

Resumen

La presente investigación nace con la finalidad de analizar las percepciones, prácticas de uso y actitudes hacia la regulación ética de la inteligencia artificial (IA) en una institución educativa rural del departamento de Cundinamarca, Colombia, que atiende a 500 estudiantes con conectividad intermitente. Esta responde a un vacío documentado: la literatura iberoamericana sobre ética de la IA en educación se concentra en contextos urbanos y universitarios, sin producir evidencia desde la ruralidad de educación básica y media. Se empleó un diseño mixto secuencial explicativo (QUAN → qual). La fase cuantitativa aplicó un cuestionario de 42 ítems (CPAE-IA, α = 0.87) a 138 participantes 97 estudiantes de secundaria y media, 27 docentes, 14 directivos y administrativos mediante muestreo estratificado proporcional. Cuatro grupos focales (n = 24) se analizaron con análisis temático reflexivo. El 63.8 % de los estudiantes usa IA generativa al menos semanalmente, pero solo el 18.4 % ha recibido orientación ética. La correlación entre formación docente en competencias éticas digitales e integración pedagógica responsable fue significativa (r = 0.61, p < .001). El modelo de regresión múltiple (R² = .543) identificó el conocimiento ético previo (β = 0.48) y la percepción de riesgo sobre privacidad (β = 0.39) como predictores principales de actitudes favorables hacia la regulación; la frecuencia de uso no fue predictora. Las categorías cualitativas revelan naturalización del uso de IA sin comprensión de mecanismos de sesgo ni de las condiciones de tratamiento de datos personales. Los resultados aportan evidencia para diseñar políticas de formación ética en contextos rurales latinoamericanos.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Akgun, S. y Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(4), 431-440. https://doi.org/10.1007/s43681-021-00096-7 DOI: https://doi.org/10.1007/s43681-021-00096-7

Braun, V. y Clarke, V. (2022). Thematic analysis: A practical guide. SAGE Publications. DOI: https://doi.org/10.4135/9781036232078.n9

Cabero-Almenara, J., Romero-Tena, R. y Palacios-Rodríguez, A. (2024). Digital competence of university teachers and its relationship with the use of artificial intelligence. Education and Information Technologies, 29(6), 7601-7624. https://doi.org/10.1007/s10639-023-12065-0 DOI: https://doi.org/10.1007/s10639-023-12065-0

CEPAL. (2022). Perspectivas económicas de América Latina 2022: Hacia una transición verde e inclusiva. Comisión Económica para América Latina y el Caribe. https://doi.org/10.1787/3eae2082-es

Celik, I., Dindar, M., Muukkonen, H. y Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616-630. https://doi.org/10.1007/s11528-022-00715-y DOI: https://doi.org/10.1007/s11528-022-00715-y

Chaudhry, I. S. y Kazim, E. (2022). Artificial intelligence in education (AIEd): A high-level academic and industry note 2021. AI and Society, 37(4), 1617-1622. https://doi.org/10.1007/s00146-021-01191-2

Creswell, J. W. y Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5.ª ed.). SAGE Publications.

Crompton, H. y Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8 DOI: https://doi.org/10.1186/s41239-023-00392-8

Duan, Y., Edwards, J. S. y Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data. International Journal of Information Management, 48, 63-71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.01.021

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B. y Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 DOI: https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Floridi, L., Cowls, J., King, T. C. y Taddeo, M. (2021). How to design AI for social good: Seven essential factors. Science and Engineering Ethics, 26(3), 1771-1796. https://doi.org/10.1007/s11948-020-00213-5 DOI: https://doi.org/10.1007/s11948-020-00213-5

Greene, J. C., Caracelli, V. J. y Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11(3), 255-274. https://doi.org/10.3102/01623737011003255 DOI: https://doi.org/10.3102/01623737011003255

Hair, J. F., Black, W. C., Babin, B. J. y Anderson, R. E. (2019). Multivariate data analysis (8.ª ed.). Cengage Learning.

Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I. y Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide agenda. International Journal of Artificial Intelligence in Education, 32(2), 504-526. https://doi.org/10.1007/s40593-021-00271-2 DOI: https://doi.org/10.1007/s40593-021-00239-1

Kabudi, T., Pappas, I. y Olsen, D. H. (2021). AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers and Education: Artificial Intelligence, 2, 100017. https://doi.org/10.1016/j.caeai.2021.100017 DOI: https://doi.org/10.1016/j.caeai.2021.100017

Knox, J. (2020). Artificial intelligence and education in China. Learning, Media and Technology, 45(3), 298-311. https://doi.org/10.1080/17439884.2020.1754236 DOI: https://doi.org/10.1080/17439884.2020.1754236

Krasadaki, E. (2023). AI literacy in primary education: Exploring student perceptions and knowledge. Education and Information Technologies, 28(9), 11713-11731. https://doi.org/10.1007/s10639-023-11658-x DOI: https://doi.org/10.1007/s10639-022-11551-1

Lee, I. y Kwon, K. (2023). Addressing ethical dimensions of AI in K-12 education: A framework and review. Journal of Research in Science Teaching, 60(4), 873-907. https://doi.org/10.1002/tea.21835 DOI: https://doi.org/10.1002/tea.21835

Long, D. y Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-16. https://doi.org/10.1145/3313831.3376727 DOI: https://doi.org/10.1145/3313831.3376727

Luckin, R., Cukurova, M., Kent, C. y du Boulay, B. (2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076 DOI: https://doi.org/10.1016/j.caeai.2022.100076

Mah, D.-K. e Ifenthaler, D. (2023). Academic staff perspectives on first-year students' academic competencies. Journal of Applied Research in Higher Education, 15(1), 45-59. https://doi.org/10.1108/JARHE-06-2021-0218

Morales-Morgado, E. M., Santos-Sancho, J. M. y Martínez-Abad, F. (2022). Valoración de competencias informacionales en estudiantes universitarios mediante análisis de redes sociales. Revista Española de Documentación Científica, 45(1), e319. https://doi.org/10.3989/redc.2022.1.1821

Obermeyer, Z., Powers, B., Vogeli, C. y Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. https://doi.org/10.1126/science.aax2342 DOI: https://doi.org/10.1126/science.aax2342

OCDE. (2023). PISA 2022 results: Fit for the future (Vol. I). OECD Publishing. https://doi.org/10.1787/53f23881-en DOI: https://doi.org/10.1787/53f23881-en

Pedro, F., Subosa, M., Rivas, A. y Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000366994

Pereira, J., Fernandez-Raga, M., Fernandez-Ramirez, B., Saavedra, D. y Rodriguez, A. (2022). Artificial intelligence in education: A review of challenges and opportunities. Sustainability, 14(21), 13850. https://doi.org/10.3390/su142113850 DOI: https://doi.org/10.3390/su142113850

Popenici, S. A. D. y Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 22. https://doi.org/10.1186/s41039-017-0062-8 DOI: https://doi.org/10.1186/s41039-017-0062-8

Reglamento de IA de la Unión Europea [AI Act]. Reglamento (UE) 2024/1689 del Parlamento Europeo y del Consejo. (2024, 13 de junio). Diario Oficial de la Unión Europea, L 1689. https://eur-lex.europa.eu/legal-content/ES/TXT/?uri=CELEX%3A32024R1689

Renz, A. y Hilbig, R. (2021). Prerequisites for artificial intelligence in further education: Identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 18(1), 1-21. https://doi.org/10.1186/s41239-021-00258-3 DOI: https://doi.org/10.1186/s41239-021-00245-2

Romero-Rodríguez, L. M., Torres-Toukoumidis, Á., Aguaded, I. y Hernández-Serrano, M. J. (2023). Implicaciones pedagógicas del uso de IA generativa en la educación superior: una revisión sistemática. Pixel-Bit. Revista de Medios y Educación, 68, 7-30. https://doi.org/10.12795/pixelbit.101148

Selwyn, N. (2022). The future of AI and education: Some cautionary notes. European Journal of Education, 57(4), 620-631. https://doi.org/10.1111/ejed.12532 DOI: https://doi.org/10.1111/ejed.12532

Southgate, E. (2020). Artificial intelligence, ethics, equity and higher education: A (fairly) brief primer. National Centre for Student Equity in Higher Education. https://www.ncsehe.edu.au/publications/ai-equity-he-primer/

Taddeo, M. y Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751-752. https://doi.org/10.1126/science.aat5991 DOI: https://doi.org/10.1126/science.aat5991

Tashakkori, A. y Teddlie, C. (2021). SAGE handbook of mixed methods in social & behavioral research (3.ª ed.). SAGE Publications.

Tuomi, I. (2023). The impact of artificial intelligence on learning, teaching and education: Policies for the future. Publications Office of the European Union. https://doi.org/10.2760/153756

UNESCO. (2021). Recommendation on the ethics of artificial intelligence. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000381137

UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693

Williamson, B. y Hogan, A. (2020). Commercialisation and privatisation in/of education in the context of Covid-19. Education International. https://www.ei-ie.org/en/item/23137

Williamson, B., Eynon, R. y Potter, J. (2020). Pandemic politics, pedagogies and practices: Digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2), 107-114. https://doi.org/10.1080/17439884.2020.1761641 DOI: https://doi.org/10.1080/17439884.2020.1761641

Zawacki-Richter, O., Marín, V. I., Bond, M. y Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education — Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0 DOI: https://doi.org/10.1186/s41239-019-0171-0

Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

Descargas

Publicado

2026-09-25

Cómo citar

Mejía Casas, R. L., Gamboa Murillo, M. D., & Bustos Chiliquinga, B. C. (2026). Ética e inteligencia artificial en entornos educativos rurales: percepciones, prácticas y brechas regulatorias en una institución colombiana. Saber Estratégico Internacional, 4(3), 1371–1389. https://doi.org/10.70577/s.e.v4i3.130

Artículos similares

<< < 4 5 6 7 8 9 10 11 > >> 

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