La importancia de la inteligencia artificial en el fomento de las competencias profesionales del futuro: una revisión sistemática

Autores/as

DOI:

https://doi.org/10.46502/issn.1856-7576/2025.19.02.19

Palabras clave:

automatización, pensamiento crítico, oportunidades, riesgos, competencia profesional, proceso educativo

Resumen

El objetivo de este estudio es realizar una revisión sistemática de materiales relevantes publicados entre 2018 y 2025, centrada en analizar las ventajas y desventajas de la adopción de la inteligencia artificial (IA). Se aplicaron las directrices PRISMA para la búsqueda, selección y análisis parcial de la literatura científica. Se seleccionaron 54 fuentes, entre ellas artículos experimentales, estudios de revisión, monografías, actas de congresos y artículos analíticos. La revisión sistemática se llevó a cabo en tres fases: (1) lectura analítica, (2) cribado y (3) examen e informe. Los resultados muestran que numerosos estudios destacan los beneficios potenciales de las tecnologías emergentes desde la etapa escolar, así como la preparación del profesorado para integrarlas de manera creativa. Del total de estudios revisados, el 39 % fueron investigaciones experimentales y el 36 % revisiones teóricas. La mayoría se desarrollaron en instituciones de educación superior con participación de estudiantes y docentes. Metodológicamente, predominaron las investigaciones teóricas y basadas en encuestas, aunque los estudios experimentales también fueron significativos. Las conclusiones indican que, dada la rápida evolución de las tecnologías digitales, un enfoque integral que combine investigación empírica y teórica resulta óptimo para evaluar el impacto de la IA en la formación de competencias profesionales.

Biografía del autor/a

Valeriia Molodtsova, National University "Odesa Maritime Academy", Odesa, Ukraine.

PhD in Pedagogy, Associate Professor at the Department of English in Marine Engineering, Educational and Scientific Institute of Engineering, National University "Odesa Maritime Academy", Odesa, Ukraine.

Nataliia Hrechanyk, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.

Doctor of Pedagogical Sciences, Professor of the Department of Management and Educational Technology, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.

Ren Guoxi, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.

Graduate student of the Department of Pedagogy, Education and Educational Sciences, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine.

Olena Khoroshailo, LLC “Technical University "Metinvest Polytechnic", Zaporizhzhia, Ukraine.

Candidate of Pedagogical Sciences, Associate Professor, Department of Language and Humanitarian Disciplines, LLC “Technical University "Metinvest Polytechnic", Zaporizhzhia, Ukraine.

Iryna Fadyeyeva, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.

Doctor of Economics, habilitated, Professor, Department of Finance, Accounting and Taxes, Institute of Economics and Management, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine.

Citas

An, Y., Kaplan-Rakowski, R., Yang, J., Nanni, A., & Wang, Y. (2021). Examining K-12 teachers’ feelings, experiences, and perspectives regarding online teaching during the early stage of the COVID-19 pandemic. Educational Technology Research and Development, 69(5), 2589–2613. https://doi.org/10.1007/s11423-021-10008-5

Baidoo-Anu, D., Asamoah, D., Amoako, I., & Mahama, I. (2024). Exploring student perspectives on generative artificial intelligence in higher education learning. Discover Education, 3(1). https://doi.org/10.1007/s44217-024-00173-z

Berendt, B., Littlejohn, A., & Blakemore, M. (2020). AI in education: learner choice and fundamental rights. Learning, Media and Technology, 45(3), 312–324. https://doi.org/10.1080/17439884.2020.1786399

Bingham, C. (2024). Education and Artificial Intelligence at the Scene of Writing: A Derridean Consideration. Futurity Philosophy, 3(4), 34–46. https://doi.org/10.57125/fp.2024.12.30.03

Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: Mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18(1), 50. https://doi.org/10.1186/s41239-021-00282-x

Brauner, S., Murawski, M., & Bick, M. (2025). The development of a competence framework for artificial intelligence professionals using probabilistic topic modelling. Journal of Enterprise Information Management, 38(1), 197–218. https://doi.org/10.1108/JEIM-09-2022-0341

Catchpoole, V. (2022). Refocusing Educational Practice Through an Ethic of Care. In The Palgrave Handbook of Educational Leadership and Management Discourse (pp. 503–523). Springer International Publishing. https://doi.org/10.1007/978-3-030-99097-8_88

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8

Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16–24. https://doi.org/10.1016/j.procs.2018.08.233

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

Ciolacu, M., Tehrani, A. F., Binder, L., & Svasta, P. M. (2018). Education 4.0 – Artificial intelligence assisted higher education: Early recognition system with machine learning to support students' success. In 2018 IEEE 24th International Symposium for Design and Technology in Electronic Packaging (SIITME) (pp. 23–30). IEEE. https://doi.org/10.1109/SIITME.2018.8599203

Dai, Y., Chai, C.-S., Lin, P.-Y., Jong, M. S.-Y., Guo, Y., & Qin, J. (2020). Promoting Students’ Well-Being by Developing Their Readiness for the Artificial Intelligence Age. Sustainability, 12(16), 6597. https://doi.org/10.3390/su12166597

de la Torre, A., & Baldeon-Calisto, M. (2024). Generative Artificial Intelligence in Latin American Higher Education: A Systematic Literature Review. In 2024 12th International Symposium on Digital Forensics and Security (ISDFS). IEEE. https://doi.org/10.1109/isdfs60797.2024.10527283

Elmahdi, I., Al-Hattami, A., & Fawzi, H. (2018). Using technology for formative assessment to improve students' learning. Turkish Online Journal of Educational Technology, 17(2), 182–188. https://eric.ed.gov/?id=EJ1176157

Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022). The impact of a virtual teaching assistant (chatbot) on students' learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(1). https://doi.org/10.1186/s41239-022-00362-6

Fahimirad, M., & Kotamjani, S. S. (2018). A Review on Application of Artificial Intelligence in Teaching and Learning in Educational Contexts. International Journal of Learning and Development, 8(4), 106. https://doi.org/10.5296/ijld.v8i4.14057

Fidalgo, P., Thormann, J., Kulyk, O., & Lencastre, J. A. (2020). Students’ perceptions on distance education: A multinational study. International Journal of Educational Technology in Higher Education, 17(1). https://doi.org/10.1186/s41239-020-00194-2

Fuchs, K., & Aguilos, V. (2023). Integrating Artificial Intelligence in Higher Education: Empirical Insights from Students about Using ChatGPT. International Journal of Information and Education Technology, 13(9), 1365–1371. https://doi.org/10.18178/ijiet.2023.13.9.1939

Guerrero-Quiñonez, A. J., Bedoya-Flores, M. C., Mosquera-Quiñonez, E. F., Mesías-Simisterra, Á. E., & Bautista-Sánchez, J. V. (2023). Artificial Intelligence and its scope in Latin American higher education. Ibero-American Journal of Education & Society Research, 3(1), 264–271. https://doi.org/10.56183/iberoeds.v3i1.627

Gutierrez, S. S. M., Perez, S. L., & Munguia, M. G. (2022). Artificial Intelligence in e-Learning Plausible Scenarios in Latin America and New Graduation Competencies. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, 17(1), 31–40. https://doi.org/10.1109/rita.2022.3149833

Hryhorak, M., Harmash, O., & Popkowski, T. (2023). Artificial intelligence in supply chain management: opportunities and threats for professional competence. Electronic Scientific Journal Intellectualization of Logistics and Supply Chain Management, (19), 24–44. https://doi.org/10.46783/smart-scm/2023-19-3

Huang, Y. (2023). Ethics and educational technology: Reflection, interrogation, and design as a framework for practice. edited by Stephanie L. Moore and Heather K. Tillberg-Webb. New York, NY: Routledge. https://doi.org/10.1080/00131857.2023.2255370

Huang, R., Ritzhaupt, A. D., Sommer, M., Zhu, J., Stephen, A., Valle, N., Hampton, J., & Li, J. (2020). The impact of gamification in educational settings on student learning outcomes: a meta-analysis. Educational Technology Research and Development, 68(4), 1875–1901. https://doi.org/10.1007/s11423-020-09807-z

Jain, K., & Raghuram, J. N. V. (2023). Unlocking potential: The impact of AI on education technology. Multidisciplinary Reviews, 7(3), 2024049. https://doi.org/10.31893/multirev.2024049

Joo, Y. J., Park, S., & Lim, E. (2018). Factors Influencing Preservice Teachers’ Intention to Use Technology. Educational Technology & Society, 21(3), 48–59. https://www.jstor.org/stable/26458506

Khoroshailo, O., & Kocherhina, S. (2023). Use of artificial intelligence to improve the quality of teaching foreign languages in a higher educational institution. Pedagogical sciences reality and perspectives, (93), 123–127. https://doi.org/10.31392/npu-nc.series5.2023.93.25

Khudoliy, L., & Voitsekhivska, V. (2015). Control as an effective implementation of the national target program. Management Theory and Studies for Rural Business and Infrastructure Development, 37(1), 60–69. https://doi.org/10.15544/mts.2015.06

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

Kokku, R., Sundararajan, S., Dey, P., Sindhgatta, R., Nitta, S., & Sengupta, B. (2018). Augmenting classrooms with AI for personalized education. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6976–6980). IEEE. https://doi.org/10.1109/ICASSP.2018.8461812

Kumar, N. (2024). Innovative Approaches of E-Learning in College Education: Global Experience. E-Learning Innovations Journal, 2(2), 36–51. https://doi.org/10.57125/elij.2024.09.25.03

Kurebay, B., Saginovna, S. S., Khassanova, I., Kazetova, A., Bayukanskaya, S., & Mailybaeva, G. (2023). Competence of Primary School Teachers in the Use of Internet Resources. International Journal of Education in Mathematics, Science and Technology, 11(4), 964–980. https://doi.org/10.46328/ijemst.3466

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

Makransky, G., & Lilleholt, L. (2018). A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educational Technology Research and Development, 66(5), 1141–1164. https://doi.org/10.1007/s11423-018-9581-2

Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The Impact of Artificial Intelligence on Workers’ Skills: Upskilling and Reskilling in Organisations. Informing Science: The International Journal of an Emerging Transdiscipline, 26, 039–068. https://doi.org/10.28945/5078

Muraina, I. O., Hojapoji, G. S., & Amao, A. O. (2025). Adoption of Metacognitive Approach to Teaching and Learning of Programming Language Concepts to Undergraduate and Graduate University Students. Futurity of Social Sciences, 3(1), 73–90. https://doi.org/10.57125/fs.2025.03.20.05

Nafea, I. T. (2018). Machine Learning in Educational Technology. In Machine Learning - Advanced Techniques and Emerging Applications. InTech. https://doi.org/10.5772/intechopen.72906

Omelchuk, M., Maksymchuk, B., Ihnatenko, S., Navolskyi, N., Kitsak, T., Vitkovskyi, O., Ostrovska, N., Vykhrushch, A., Lukashchuk, M., Lukashchuk, I., Demianchuk, M., Khmeliar, I., Kushnir, L., & Maksymchuk, I. (2022). Developing Professional Competency in First Aid in Future Coaches in Ukraine. Romanian Journal for Multidimensional Education, 14(3), 392–411. https://doi.org/10.18662/rrem/14.3/615

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., & Moher, D. (2021). Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement. Journal of Clinical Epidemiology, 134, 103–112. https://doi.org/10.1016/j.jclinepi.2021.02.003

Ramadhona, N., Putri, A. A., & Wuisan, D. S. S. (2022). Students' Opinions of the Use of Quipper School as an Online Learning Platform for Teaching English. International Transactions on Education Technology (ITEE), 1(1), 35–41. https://doi.org/10.34306/itee.v1i1.180

Rodríguez Illera, J. L. (2024). AI in the discourse of the relationships between technology and education. Digital Education Review, (45), 1–7. https://doi.org/10.1344/der.2024.45.1-7

Salas-Pilco, S. Z., & Yang, Y. (2022). Artificial intelligence applications in Latin American higher education: a systematic review. International Journal of Educational Technology in Higher Education, 19(1). https://doi.org/10.1186/s41239-022-00326-w

Sharma, A., & Sharma, R. (2025). Bibliometric exploration of artificial intelligence applications in healthcare: trends and future directions. Journal of Public Health and Development, 23(2), 281–303. https://doi.org/10.55131/jphd/2025/230220

Sijing, L., & Lan, W. (2018). Artificial intelligence education: Ethical problems and solutions. In 2018 13th International Conference on Computer Science & Education (ICCSE) (pp. 1–5). IEEE. https://doi.org/10.1109/ICCSE.2018.8468773

Siraj-Blatchford, J. (2023). How artificial intelligence could shape early years education. Early Years Educator, 24(5), 34–35. https://doi.org/10.12968/eyed.2023.24.5.34

Song, P., & Wang, X. (2020). A bibliometric analysis of worldwide educational artificial intelligence research development in recent twenty years. Asia Pacific Education Review, 21(3), 473–486. https://doi.org/10.1007/s12564-020-09640-2

Stolpe, K., & Hallström, J. (2024). Artificial Intelligence Literacy for Technology Education. Computers and Education Open, 6, 100159. https://doi.org/10.1016/j.caeo.2024.100159

Tuma, F. (2021). The use of educational technology for interactive teaching in lectures. Annals of Medicine and Surgery, 62, 231–235. https://doi.org/10.1016/j.amsu.2021.01.051

Turchyn, I., Zaitseva, S., Rudenko, N., Saienko, V., Kuzemko, N., & Denefil, O. (2023). Using Distance Learning Models as Opportunities for Blended Learning for Foreigners. Romanian Journal for Multidimensional Education, 15(4), 178–191. https://doi.org/10.18662/rrem/15.4/787

Webb, M. E., Fluck, A., Magenheim, J., Malyn-Smith, J., Waters, J., Deschênes, M., & Zagami, J. (2020). Machine learning for human learners: opportunities, issues, tensions and threats. Educational Technology Research and Development, 69(4), 2109-2130. https://doi.org/10.1007/s11423-020-09858-2

Winters, N., Eynon, R., Geniets, A., Robson, J., & Kahn, K. (2019). Can we avoid digital structural violence in future learning systems? Learning, Media and Technology, 45(1), 17–30. https://doi.org/10.1080/17439884.2020.1708099

Xu, W., & Ouyang, F. (2022). The application of AI technologies in STEM education: a systematic review from 2011 to 2021. International Journal of STEM Education, 9(1). https://doi.org/10.1186/s40594-022-00377-5

Yi, H., Liu, T., & Lan, G. (2024). The key artificial intelligence technologies in early childhood education: a review. Artificial Intelligence Review, 57(1). https://doi.org/10.1007/s10462-023-10637-7

Zhai, X., Shi, L., & Nehm, R. H. (2021a). A meta-analysis of machine learning-based science assessments: Factors impacting machine-human score agreements. Journal of Science Education and Technology, 30(3), 361–379. https://doi.org/10.1007/s10956-020-09875-z

Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021b). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 2021, 1–18. https://doi.org/10.1155/2021/8812542

Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2, 100025. https://doi.org/10.1016/j.caeai.2021.100025

Zhu, Y., Zhang, J. H., Au, W., & Yates, G. (2020). University students’ online learning attitudes and continuous intention to undertake online courses: a self-regulated learning perspective. Educational Technology Research and Development: ETR & D, 68(3), 1485–1519. https://doi.org/10.1007/s11423-020-09753-w

Publicado

2025-06-30

Cómo citar

Molodtsova, V., Hrechanyk, N., Guoxi, R., Khoroshailo, O., & Fadyeyeva, I. (2025). La importancia de la inteligencia artificial en el fomento de las competencias profesionales del futuro: una revisión sistemática. Revista Eduweb, 19(2), 280–295. https://doi.org/10.46502/issn.1856-7576/2025.19.02.19

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