Uso de la Inteligencia Artificial para Mejorar el Aprendizaje de Estudiantes de Octavo Año
Palabras clave:
inteligencia artificial, educación, aprendizaje personalizado, retroalimentación educativa
Resumen
El objetivo de esta revisión sistemática es reconocer, compendiar y evaluar de manera crítica la literatura sobre la aplicación de la inteligencia artificial (IA) en la mejora del aprendizaje de los estudiantes de octavo año. A través del método PRISMA, se llevaron a cabo búsquedas exhaustivas en las bases de datos Web of Science y Scopus, enfocándose en estudios publicados entre 2019 y 2024. En total, se incluyeron diez estudios que evidenciaron cómo las herramientas de IA tienen la capacidad de personalizar el aprendizaje y mejorar significativamente la retroalimentación, resultando en mejores resultados académicos. Asimismo, se determinó que la formación continua de los docentes en competencias digitales es fundamental para la adopción efectiva de estas tecnologías. Los resultados apoyan las teorías de aprendizaje constructivista y adaptativo, proponiendo orientaciones prácticas para la integración de la IA en la educación. A pesar de que los resultados son alentadores, se requiere realizar estudios a largo plazo y en diversos contextos culturales para validar y ampliar estos hallazgos. Esta revisión proporciona una base sólida para la toma de decisiones informadas y la implementación de prácticas educativas innovadoras, garantizando el uso efectivo de tecnologías avanzadas para mejorar el aprendizaje y el rendimiento académico.
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Citas
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Gao, R., Merzdorf, H. E., Anwar, S., Hipwell, M. C., & Srinivasa, A. R. (2024). Automatic assessment of text-based responses in post-secondary education: A systematic review. Computers and Education: Artificial Intelligence, 6, 100206. https://doi.org/10.1016/j.caeai.2024.100206
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https://doi.org/10.1177/11206721231215862
Katuka, G. A., Chakraburty, S., Lee, H., Dhama, S., Earle-Randell, T., Celepkolu, M., Boyer, K. E., Glazewski, K., Hmelo-Silver, C., & Mcklin, T. (2024). Integrating Natural Language Processing in Middle School Science Classrooms: An Experience Report. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, 639–645.
https://doi.org/10.1145/3626252.3630881
Khan, S., Iqbal, M., Osho, O., Singh, K., Derrick, K., Nelson, P., Li, L., Sidnam-Mauch, E., Bannister, N., Caine, K., & Knijnenburg, B. (2024). Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive Personalization: A Classroom Intervention Using Design-Based Research. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–26.
https://doi.org/10.1145/3613904.3642460
Kumar, P., S, N., A, S., & K B, K. (2023). Implementation of Artificial Intelligence in Education. International Research Journal of Computer Science, 10(05), 104–108.
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Lawrence, L., Echeverria, V., Yang, K., Aleven, V., & Rummel, N. (2024). How teachers conceptualise shared control with anAI co‐orchestration tool: A multiyear teacher‐centred design process. British Journal of Educational Technology, 55(3), 823–844.
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Agrela Rodrigues, F. de A., Grizel Morales, N., Paco Carvajal, R., Velasco Valverde, D., Mayta Cruz, M., Avendaño Endara, E., & Simons Aparicio, C. P. (2025). Desafíos en el Desarrollo Lingüístico y Cognitivo en una Niña con Sordera Profunda: Estudio de Caso de Maria . I+D Internacional Revista Científica Y Académica , 4(1), 65–77. https://doi.org/10.63636/3078-1639.v4.n1.27
Agrela Rodrigues, F. de A. (2025). A Relação entre os Neurotransmissores Excitatórios, como o Aspartato e o Glutamato, e o Transtorno do Déficit de Atenção com Hiperatividade (TDAH). Ciencia Y Reflexión, 4(1), 2686–2700. https://doi.org/10.70747/cr.v4i1.306
González Coronel , F. A., Veloso Bogarín, J. M., & Gauna Quiñones, C. E. (2025). Impacto de las Nuevas Tecnologías de la Información y Comunicación (TIC) en el proceso de Enceñanza y Aprendizaje del Instituto de Formación Docente-Gral. José Eduvigis Díaz 2024. Ciencia Latina Revista Científica Multidisciplinar, 9(2), 6916-6934. https://doi.org/10.37811/cl_rcm.v9i2.17414
Chicaiza Valle, V. L., Campos Guillén, M. F., Cadena Pasquel, A. P., & Chicaiza Rosero, M. L. (2025). Estrategias para Fomentar la Inteligencia Emocional y Mejorar la Comprensión en el Aula de Primaria. Estudios Y Perspectivas Revista Científica Y Académica , 5(2), 706–735. https://doi.org/10.61384/r.c.a.v5i2.1155
Escalante Jiménez, J. L., Rodríguez Colón, P. L., & Polanco García, C. Y. (2025). Inteligencia artificial en contextos educativos: un acercamiento desde una revisión documental sistemática. Ciencia Y Reflexión, 4(2), 325–349. https://doi.org/10.70747/cr.v4i2.241
Liu, S., McCoy, A. B., Peterson, J. F., Lasko, T. A., Sittig, D. F., Nelson, S. D., Andrews, J., Patterson, L., Cobb, C. M., Mulherin, D., Morton, C. T., & Wright, A. (2024). Leveraging explainable artificial intelligence to optimize clinical decision support. Journal of the American Medical Informatics Association, 31(4), 968–974. https://doi.org/10.1093/jamia/ocae019
Martin, F., Vahedian Movahed, S., Dimino, J., Farrell, A., Irankhah, E., Ghosh, S., Jain, G., Mahipal, V., Rayavaram, P., Temitayo Sanusi, I., Salas, E., Wolkowicz, K., & Narain, S. (2024). Perception, Trust, Attitudes, and Models: Introducing Children to AI and Machine Learning with Five Software Exhibits. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 1740–1741. https://doi.org/10.1145/3626253.3635512
Martins, R. M., & Gresse von Wangenheim, C. (2023). Teaching Computing to Middle and High School Students from a Low Socio-Economic Status Background: A Systematic Literature Review. Informatics in Education. https://doi.org/10.15388/infedu.2024.01
Ng, D. T. K., Tan, C. W., & Leung, J. K. L. (2024). Empowering student self‐regulated learning and science education throughChatGPT : A pioneering pilot study. British Journal of Educational Technology, 55(4), 1328–1353. https://doi.org/10.1111/bjet.13454
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Shardeo, V., Sarkar, B. D., Mir, U. B., & Kaushik, P. (2024). Adoption of Metaverse in Healthcare Sector: An Empirical Analysis of its Enablers. IEEE Transactions on Engineering Management, 71, 8671–8685. https://doi.org/10.1109/TEM.2024.3400401
Siyao, L., Ya, W., & Yingfeng, L. (2024). How can industrial intelligence change the employment structure of the floating population? PLOS ONE, 19(5), e0297266.
https://doi.org/10.1371/journal.pone.0297266
Su, J., & Yang, W. (2024).AI literacy curriculum and its relation to children’s perceptions of robots and attitudes towards engineering and science: An intervention study in early childhood education. Journal of Computer Assisted Learning, 40(1), 241–253.
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Tan, M., & Subramonyam, H. (2024). More than Model Documentation: Uncovering Teachers’ Bespoke Information Needs for Informed Classroom Integration of ChatGPT. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–19.
https://doi.org/10.1145/3613904.3642592
Yahagi, M., Hiruta, R., Miyauchi, C., Tanaka, S., Taguchi, A., & Yaguchi, Y. (2024). Comparison of Conventional Anesthesia Nurse Education and an Artificial Intelligence Chatbot (ChatGPT) Intervention on Preoperative Anxiety: A Randomized Controlled Trial. Journal of PeriAnesthesia Nursing. https://doi.org/10.1016/j.jopan.2023.12.005
Yuan, H., Zheng, Z., Gu, Y., Zhou, J., & Chen, Y. (2024). ExpT: Online Action Detection via Exemplar-Enhanced Transformer for Secondary School Experimental Evaluation (pp. 347–356).
https://doi.org/10.1007/978-981-97-0791-1_30
Zeller, A., Gutenberg, J., Niebauer, J., Crutzen, R., & Kulnik, S. T. (2024). Patients’ experiences and perspectives regarding the use of digital technology to support exercise-based cardiac rehabilitation: a qualitative interview study. Frontiers in Sports and Active Living, 6.
https://doi.org/10.3389/fspor.2024.1371652
Zhang, H., Lee, I., & Moore, K. (2024). An Effectiveness Study of Teacher-Led AI Literacy Curriculum in K-12 Classrooms. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23318–23325. https://doi.org/10.1609/aaai.v38i21.30380
Zheng, Z., Wang, B., Wang, Z., Chen, Y., Zhou, J., & Kong, L. (2024). Automated Analysis of Chemistry Experiment Videos: New Challenges for Video Understanding (pp. 194–201).
https://doi.org/10.1007/978-981-97-0730-0_18
https://doi.org/10.1007/978-981-99-1767-9_42
Alqahtani, T., Badreldin, H. A., Alrashed, M., Alshaya, A. I., Alghamdi, S. S., bin Saleh, K., Alowais, S. A., Alshaya, O. A., Rahman, I., Al Yami, M. S., & Albekairy, A. M. (2023). The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research. Research in Social and Administrative Pharmacy, 19(8), 1236–1242.
https://doi.org/10.1016/j.sapharm.2023.05.016
Alsheyab, M. S. A. (2024). Legal analysis of the merits of electronic transferable records: toward cross-border trade digitalization. International Journal of Law and Management.
https://doi.org/10.1108/IJLMA-09-2023-0209
Chervonski, E., Harish, K. B., Rockman, C. B., Sadek, M., Teter, K. A., Jacobowitz, G. R., Berland, T. L., Lohr, J., Moore, C., & Maldonado, T. S. (2024). Generative artificial intelligence chatbots may provide appropriate informational responses to common vascular surgery questions by patients. Vascular. https://doi.org/10.1177/17085381241240550
Cowit, N. Q., & Fiesler, C. (2024). Student Preconceptions of Artificial Intelligence: Results from Single Institution Survey. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 1610–1611. https://doi.org/10.1145/3626253.3635484
Dai, C.-P., & Ke, F. (2022). Educational applications of artificial intelligence in simulation-based learning: A systematic mapping review. Computers and Education: Artificial Intelligence, 3, 100087. https://doi.org/10.1016/j.caeai.2022.100087
Demartini, C. G., Sciascia, L., Bosso, A., & Manuri, F. (2024). Artificial Intelligence Bringing Improvements to Adaptive Learning in Education: A Case Study. Sustainability, 16(3), 1347.
https://doi.org/10.3390/su16031347
Gao, R., Merzdorf, H. E., Anwar, S., Hipwell, M. C., & Srinivasa, A. R. (2024). Automatic assessment of text-based responses in post-secondary education: A systematic review. Computers and Education: Artificial Intelligence, 6, 100206. https://doi.org/10.1016/j.caeai.2024.100206
Gurnani, B., & Kaur, K. (2024). Leveraging ChatGPT for ophthalmic education: A critical appraisal. European Journal of Ophthalmology, 34(2), 323–327.
https://doi.org/10.1177/11206721231215862
Katuka, G. A., Chakraburty, S., Lee, H., Dhama, S., Earle-Randell, T., Celepkolu, M., Boyer, K. E., Glazewski, K., Hmelo-Silver, C., & Mcklin, T. (2024). Integrating Natural Language Processing in Middle School Science Classrooms: An Experience Report. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1, 639–645.
https://doi.org/10.1145/3626252.3630881
Khan, S., Iqbal, M., Osho, O., Singh, K., Derrick, K., Nelson, P., Li, L., Sidnam-Mauch, E., Bannister, N., Caine, K., & Knijnenburg, B. (2024). Teaching Middle Schoolers about the Privacy Threats of Tracking and Pervasive Personalization: A Classroom Intervention Using Design-Based Research. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–26.
https://doi.org/10.1145/3613904.3642460
Kumar, P., S, N., A, S., & K B, K. (2023). Implementation of Artificial Intelligence in Education. International Research Journal of Computer Science, 10(05), 104–108.
https://doi.org/10.26562/irjcs.2023.v1005.01
Lawrence, L., Echeverria, V., Yang, K., Aleven, V., & Rummel, N. (2024). How teachers conceptualise shared control with an
https://doi.org/10.1111/bjet.13372
Murillo Zavala, A. M., Cañarte Castro, E. M., & Verduga Toala , M. M. (2025). Malnutrición y deficiencias hematológicas en mujeres en edad fértiles . Arandu UTIC, 12(1), 4480–4494. https://doi.org/10.69639/arandu.v12i1.906
Agrela Rodrigues, F. de A., Grizel Morales, N., Paco Carvajal, R., Velasco Valverde, D., Mayta Cruz, M., Avendaño Endara, E., & Simons Aparicio, C. P. (2025). Desafíos en el Desarrollo Lingüístico y Cognitivo en una Niña con Sordera Profunda: Estudio de Caso de Maria . I+D Internacional Revista Científica Y Académica , 4(1), 65–77. https://doi.org/10.63636/3078-1639.v4.n1.27
Agrela Rodrigues, F. de A. (2025). A Relação entre os Neurotransmissores Excitatórios, como o Aspartato e o Glutamato, e o Transtorno do Déficit de Atenção com Hiperatividade (TDAH). Ciencia Y Reflexión, 4(1), 2686–2700. https://doi.org/10.70747/cr.v4i1.306
González Coronel , F. A., Veloso Bogarín, J. M., & Gauna Quiñones, C. E. (2025). Impacto de las Nuevas Tecnologías de la Información y Comunicación (TIC) en el proceso de Enceñanza y Aprendizaje del Instituto de Formación Docente-Gral. José Eduvigis Díaz 2024. Ciencia Latina Revista Científica Multidisciplinar, 9(2), 6916-6934. https://doi.org/10.37811/cl_rcm.v9i2.17414
Chicaiza Valle, V. L., Campos Guillén, M. F., Cadena Pasquel, A. P., & Chicaiza Rosero, M. L. (2025). Estrategias para Fomentar la Inteligencia Emocional y Mejorar la Comprensión en el Aula de Primaria. Estudios Y Perspectivas Revista Científica Y Académica , 5(2), 706–735. https://doi.org/10.61384/r.c.a.v5i2.1155
Escalante Jiménez, J. L., Rodríguez Colón, P. L., & Polanco García, C. Y. (2025). Inteligencia artificial en contextos educativos: un acercamiento desde una revisión documental sistemática. Ciencia Y Reflexión, 4(2), 325–349. https://doi.org/10.70747/cr.v4i2.241
Liu, S., McCoy, A. B., Peterson, J. F., Lasko, T. A., Sittig, D. F., Nelson, S. D., Andrews, J., Patterson, L., Cobb, C. M., Mulherin, D., Morton, C. T., & Wright, A. (2024). Leveraging explainable artificial intelligence to optimize clinical decision support. Journal of the American Medical Informatics Association, 31(4), 968–974. https://doi.org/10.1093/jamia/ocae019
Martin, F., Vahedian Movahed, S., Dimino, J., Farrell, A., Irankhah, E., Ghosh, S., Jain, G., Mahipal, V., Rayavaram, P., Temitayo Sanusi, I., Salas, E., Wolkowicz, K., & Narain, S. (2024). Perception, Trust, Attitudes, and Models: Introducing Children to AI and Machine Learning with Five Software Exhibits. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 1740–1741. https://doi.org/10.1145/3626253.3635512
Martins, R. M., & Gresse von Wangenheim, C. (2023). Teaching Computing to Middle and High School Students from a Low Socio-Economic Status Background: A Systematic Literature Review. Informatics in Education. https://doi.org/10.15388/infedu.2024.01
Ng, D. T. K., Tan, C. W., & Leung, J. K. L. (2024). Empowering student self‐regulated learning and science education through
Ng, D. T. K., Xinyu, C., Leung, J. K. L., & Chu, S. K. W. (2024). Fostering students’
https://doi.org/10.1111/jcal.13009
Perrotta, C. (2024). Plug-and-Play Education. Routledge. https://doi.org/10.4324/9781003099826
Shardeo, V., Sarkar, B. D., Mir, U. B., & Kaushik, P. (2024). Adoption of Metaverse in Healthcare Sector: An Empirical Analysis of its Enablers. IEEE Transactions on Engineering Management, 71, 8671–8685. https://doi.org/10.1109/TEM.2024.3400401
Siyao, L., Ya, W., & Yingfeng, L. (2024). How can industrial intelligence change the employment structure of the floating population? PLOS ONE, 19(5), e0297266.
https://doi.org/10.1371/journal.pone.0297266
Su, J., & Yang, W. (2024).
https://doi.org/10.1111/jcal.12867
Tan, M., & Subramonyam, H. (2024). More than Model Documentation: Uncovering Teachers’ Bespoke Information Needs for Informed Classroom Integration of ChatGPT. Proceedings of the CHI Conference on Human Factors in Computing Systems, 1–19.
https://doi.org/10.1145/3613904.3642592
Yahagi, M., Hiruta, R., Miyauchi, C., Tanaka, S., Taguchi, A., & Yaguchi, Y. (2024). Comparison of Conventional Anesthesia Nurse Education and an Artificial Intelligence Chatbot (ChatGPT) Intervention on Preoperative Anxiety: A Randomized Controlled Trial. Journal of PeriAnesthesia Nursing. https://doi.org/10.1016/j.jopan.2023.12.005
Yuan, H., Zheng, Z., Gu, Y., Zhou, J., & Chen, Y. (2024). ExpT: Online Action Detection via Exemplar-Enhanced Transformer for Secondary School Experimental Evaluation (pp. 347–356).
https://doi.org/10.1007/978-981-97-0791-1_30
Zeller, A., Gutenberg, J., Niebauer, J., Crutzen, R., & Kulnik, S. T. (2024). Patients’ experiences and perspectives regarding the use of digital technology to support exercise-based cardiac rehabilitation: a qualitative interview study. Frontiers in Sports and Active Living, 6.
https://doi.org/10.3389/fspor.2024.1371652
Zhang, H., Lee, I., & Moore, K. (2024). An Effectiveness Study of Teacher-Led AI Literacy Curriculum in K-12 Classrooms. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23318–23325. https://doi.org/10.1609/aaai.v38i21.30380
Zheng, Z., Wang, B., Wang, Z., Chen, Y., Zhou, J., & Kong, L. (2024). Automated Analysis of Chemistry Experiment Videos: New Challenges for Video Understanding (pp. 194–201).
https://doi.org/10.1007/978-981-97-0730-0_18
Publicado
2025-07-14
Cómo citar
Flores Duque , S. G. (2025). Uso de la Inteligencia Artificial para Mejorar el Aprendizaje de Estudiantes de Octavo Año. Ciencia Latina Revista Científica Multidisciplinar, 9(3), 6822-6842. https://doi.org/10.37811/cl_rcm.v9i3.18326
Número
Sección
Ciencias y Tecnologías
Derechos de autor 2025 Sonia Guadalupe Flores Duque
Esta obra está bajo licencia internacional Creative Commons Reconocimiento 4.0.
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