La inteligencia artificial en educación primaria: una revisión sistemática (2000-2024)
Resumen La integración de la inteligencia artificial (IA) en la educación primaria ha despertado un gran interés debido a su potencial para transformar la enseñanza y el aprendizaje. Sin embargo, su implementación carece de una base empírica sólida que valide sus beneficios pedagógicos en esta etapa educativa. La investigación existente sigue siendo limitada, lo que plantea interrogantes fundamentales sobre cómo integrar la IA de manera efectiva y pedagógica en la educación primaria. En este contexto, el objetivo de este artículo es analizar el estado actual de la investigación sobre la IA en la educación primaria, identificando tendencias, desafíos y vacíos significativos en la literatura científica. Para ello, se realizó una revisión sistemática de la literatura publicada entre 2000 y abril de 2024, siguiendo el protocolo PRISMA. La revisión incluyó 15 estudios extraídos de las bases de datos WoS, Scopus y Dialnet, seleccionados según rigurosos criterios de calidad y relevancia. Los datos fueron analizados mediante herramientas como VOSViewer para explorar dimensiones metodológicas, pedagógicas y bibliométricas. Los hallazgos revelan una producción académica limitada centrada en áreas como la alfabetización en IA, el diseño curricular y las aplicaciones tecnológicas. No obstante, la mayoría de los estudios son descriptivos y exploratorios, con una carencia de investigaciones experimentales que evalúen el impacto real de la IA en los resultados de aprendizaje. Esta revisión subraya la necesidad urgente de estudios empíricos y de la promoción de la colaboración entre educadores, investigadores y responsables de políticas para desarrollar currículos inclusivos, éticos y basados en evidencia. Dichos esfuerzos son fundamentales para aprovechar plenamente el potencial educativo de la IA en la educación primaria.
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Cao, S., & Li, H. (2023). A Scoping Review of Digital Well-Being in Early Childhood: Definitions, Measurements, Contributors, and Interventions. International Journal of Environmental Research and Public Health, 20(4), 3510. https://doi.org/10.3390/ijerph20043510
Cheng, E. C. K., & Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in Hong Kong. Computers and Education: Artificial Intelligence, 5, 100171. https://doi.org/10.1016/j.caeai.2023.100171
Combéfis, S. (2023). Artificial Intelligence in Primary and Secondary Education: a Review of Educational Activities Development. In J.-P. Pellet & G. Parriaux (Eds.), 16th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2023 Local Proceedings (pp. 3–13). Alpen-Adria Universität Klagenfurt.
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
Dai, Y., Lin, Z., Liu, A., Dai, D., & Wang, W. (2024). Effect of an Analogy-Based Approach of Artificial Intelligence Pedagogy in Upper Primary Schools. Journal of Educational Computing Research, 61(8), 159–186. https://doi.org/10.1177/07356331231201342
Dai, Y., Liu, A., Qin, J., Guo, Y., Jong, M. S., Chai, C., & Lin, Z. (2023). Collaborative construction of artificial intelligence curriculum in primary schools. Journal of Engineering Education, 112(1), 23–42. https://doi.org/10.1002/jee.20503
Forero-Corba, W., & Negre Bennasar, F. (2023). Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: una revisión sistemática. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
Gavrilas, L., Kotsis, K. T., & Papanikolaou, M.-S. (2024). Assessing teacher readiness for educational robotics integration in primary and preschool education. Education 3-13, 1–17. https://doi.org/10.1080/03004279.2023.2300699
Hammersley, M. (2020). Reflections on the Methodological Approach of Systematic Reviews. In O. Zawacki-Richter, M. Kerres, S. Bedenlier, M. Bond, & K. Buntins (Eds.), Systematic Reviews in Educational Research (pp. 23–39). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-27602-7
Han, X., Hu, F., Xiong, G., Liu, X., Gong, X., Niu, X., Shi, W., & Wang, X. (2018). Design of AI + Curriculum for Primary and Secondary Schools in Qingdao. 2018 Chinese Automation Congress (CAC), 4135–4140. IEEE https://doi.org/10.1109/CAC.2018.8623310
Huang, X. (2022). Application of artificial intelligence APP in quality evaluation of primary school science education. Educational Studies, 50(6), 1215–1235. https://doi.org/10.1080/03055698.2022.2066462
Hyun, L. C. (2020). Analysis of Concerns in Artificial Intelligence Education for Elementary School Teachers. Journal of Korean Practical Arts Education, 26(4), 1–20. https://doi.org/10.29113/skpaer.2020.26.4.001
Iris Heung, Y. (2023). Design of Artificial Intelligence (AI) Education for Primary Schools: Arts-based Approach. In A. Kaban & A. Stachowicz-Stanusch (Eds.), Empowering Education: Exploring the Potential of Artificial Intelligence (pp. 65–90). ISTES BOOKS.
Jeon, I.-S., Jun, S.-J., & Song, K.-S. (2020). Teacher Training Program and Analysis of Teacher’s Demands to Strengthen Artificial Intelligence Education. Journal of The Korean Association of Information Education, 24(4), 279–289. https://doi.org/10.14352/jkaie.2020.24.4.279
Kaspersen, M. H., Bilstrup, K.-E. K., & Petersen, M. G. (2021). The Machine Learning Machine: A Tangible User Interface for Teaching Machine Learning. Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction, 1–12. https://doi.org/10.1145/3430524.3440638
Kim, S. (2021). Research Trends in Elementary and Secondary School Artificial Intelligence Education Using Topic Modeling and Problems in Technology Education. Korean Technology Education Association, 21(1), 106–124. https://doi.org/10.34138/KJTE.2021.21.1.106
Lin, P.-Y., Chai, C.-S., Jong, M. S.-Y., Dai, Y., Guo, Y., & Qin, J. (2021). Modeling the structural relationship among primary students’ motivation to learn artificial intelligence. Computers and Education: Artificial Intelligence, 2, 100006. https://doi.org/10.1016/j.caeai.2020.100006
Martínez-Comesaña, M., Rigueira-Díaz, X., Larrañaga-Janeiro, A., Martínez-Torres, J., Ocarranza-Prado, I., & Kreibel, D. (2023). Impact of artificial intelligence on assessment methods in primary and secondary education: Systematic literature review. Revista de Psicodidáctica (English Ed.), 28(2), 93–103. https://doi.org/10.1016/j.psicoe.2023.06.002
Masneri, S., Domínguez, A., Sanz, M., Zorrilla, M., Larrañaga, M., & Arruarte, A. (2023). cleAR: an interoperable architecture for multiuser AR-based school curricula. Virtual Reality, 27(3), 1813–1825. https://doi.org/10.1007/s10055-023-00764-5
Mertala, P., Fagerlund, J., & Calderon, O. (2022). Finnish 5th and 6th grade students’ prepre-instructional conceptions of artificial intelligence (AI) and their implications for AI literacy education. Computers and Education: Artificial Intelligence, 3, 100095. https://doi.org/10.1016/j.caeai.2022.100095
Miranda Veiga, F. J., & Valente de Andrade, A. M. (2021). Critical Success Factors in Accepting Technology in the Classroom. International Journal of Emerging Technologies in Learning (IJET), 16(18), 4. https://doi.org/10.3991/ijet.v16i18.23159
Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2023). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, 28(7), 8445–8501. https://doi.org/10.1007/s10639-022-11491-w
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
Ojeda-Bazaran, M.-J., Chamba-Eras, L., Coronel-Romero, E., Labanda-Jaramillo, M., Conde-Zhingre, L., Irene-Robalino, D., Fierro-Saltos, W., Orellana-Malla, A., Romero-Flores, M., Cueva-Alvarado, G., Chamba-Eras, I., & Erreyes-Pinzon, D. (2021). State of the Art of Teaching-Learning of Artificial Intelligence at Early Ages. 2021 XVI Latin American Conference on Learning Technologies (LACLO), (pp. 165–172). https://doi.org/10.1109/LACLO54177.2021.00024
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
Pardamean, B., Suparyanto, T., Cenggoro, T. W., Sudigyo, D., & Anugrahana, A. (2022). AI-Based Learning Style Prediction in Online Learning for Primary Education. IEEE Access, 10, 35725–35735. https://doi.org/10.1109/ACCESS.2022.3160177
Rodríguez-García, J. D., Moreno-León, J., Román-González, M., & Robles, G. (2021). Evaluation of an Online Intervention to Teach Artificial Intelligence with LearningML to 10-16-Year-Old Students. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, (pp. 177–183). ACM. https://doi.org/10.1145/3408877.3432393
Russell, S., & Norvig, P. (1994). Artificial Intelligence. A Modern Approach (Third Edition). Prentice Hall.
Sabzalieva, E., & Valentini, A. (2023). ChatGPT and Artificial Intelligence in Higher Education. UNESCO.
Shi, Y., & Rao, L. (2022). Construction of STEAM Graded Teaching System Using Backpropagation Neural Network Model under Ability Orientation. Scientific Programming, 2022(1), 7792943. https://doi.org/10.1155/2022/7792943
Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities. Computers and Education: Artificial Intelligence, 4, 100124. https://doi.org/10.1016/J.CAEAI.2023.100124
Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3, 100049. https://doi.org/10.1016/j.caeai.2022.100049
Sun-Ho, H., No, G., Yoon Tecnam, Sak, L., Eun-Jin, O., Choi, S.-K., & Oh-Woog, K. (2020). The Necessity of Using Dialog-Based Technology in Elementary English Education. Korean Journal of Elementary Education, 31, 173–186.
Tang, W., Hu, J., Zhang, H., Wu, P., & He, H. (2015). Kappa coefficient: a popular measure of rater agreement. Shanghai Archives of Psychiatry, 27(1), 62–67.
Vazhayil, A., Shetty, R., Bhavani, R. R., & Akshay, N. (2019). Focusing on Teacher Education to Introduce AI in Schools: Perspectives and Illustrative Findings. 2019 IEEE Tenth International Conference on Technology for Education (T4E), 71–77. https://doi.org/10.1109/T4E.2019.00021
Vicente-Yagüe-Jara, M. I., López-Martínez, O., Navarro-Navarro, V., & Cuéllar-Santiago, F. (2023). Writing, creativity, and artificial intelligence. ChatGPT in the university context. Comunicar, 31(77). https://doi.org/10.3916/C77-2023-04
Zhao, L., Wu, X., & Luo, H. (2022). Developing AI Literacy for Primary and Middle School Teachers in China: Based on a Structural Equation Modeling Analysis. Sustainability, 14(21), 14549. https://doi.org/10.3390/su142114549
Bowen, J. A. (2024). Teaching with AI. Johns Hopkins University Press. https://doi.org/10.56021/9781421449227
Cao, S., & Li, H. (2023). A Scoping Review of Digital Well-Being in Early Childhood: Definitions, Measurements, Contributors, and Interventions. International Journal of Environmental Research and Public Health, 20(4), 3510. https://doi.org/10.3390/ijerph20043510
Cheng, E. C. K., & Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in Hong Kong. Computers and Education: Artificial Intelligence, 5, 100171. https://doi.org/10.1016/j.caeai.2023.100171
Combéfis, S. (2023). Artificial Intelligence in Primary and Secondary Education: a Review of Educational Activities Development. In J.-P. Pellet & G. Parriaux (Eds.), 16th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2023 Local Proceedings (pp. 3–13). Alpen-Adria Universität Klagenfurt.
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
Dai, Y., Lin, Z., Liu, A., Dai, D., & Wang, W. (2024). Effect of an Analogy-Based Approach of Artificial Intelligence Pedagogy in Upper Primary Schools. Journal of Educational Computing Research, 61(8), 159–186. https://doi.org/10.1177/07356331231201342
Dai, Y., Liu, A., Qin, J., Guo, Y., Jong, M. S., Chai, C., & Lin, Z. (2023). Collaborative construction of artificial intelligence curriculum in primary schools. Journal of Engineering Education, 112(1), 23–42. https://doi.org/10.1002/jee.20503
Forero-Corba, W., & Negre Bennasar, F. (2023). Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: una revisión sistemática. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 209–253. https://doi.org/10.5944/ried.27.1.37491
Gavrilas, L., Kotsis, K. T., & Papanikolaou, M.-S. (2024). Assessing teacher readiness for educational robotics integration in primary and preschool education. Education 3-13, 1–17. https://doi.org/10.1080/03004279.2023.2300699
Hammersley, M. (2020). Reflections on the Methodological Approach of Systematic Reviews. In O. Zawacki-Richter, M. Kerres, S. Bedenlier, M. Bond, & K. Buntins (Eds.), Systematic Reviews in Educational Research (pp. 23–39). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-27602-7
Han, X., Hu, F., Xiong, G., Liu, X., Gong, X., Niu, X., Shi, W., & Wang, X. (2018). Design of AI + Curriculum for Primary and Secondary Schools in Qingdao. 2018 Chinese Automation Congress (CAC), 4135–4140. IEEE https://doi.org/10.1109/CAC.2018.8623310
Huang, X. (2022). Application of artificial intelligence APP in quality evaluation of primary school science education. Educational Studies, 50(6), 1215–1235. https://doi.org/10.1080/03055698.2022.2066462
Hyun, L. C. (2020). Analysis of Concerns in Artificial Intelligence Education for Elementary School Teachers. Journal of Korean Practical Arts Education, 26(4), 1–20. https://doi.org/10.29113/skpaer.2020.26.4.001
Iris Heung, Y. (2023). Design of Artificial Intelligence (AI) Education for Primary Schools: Arts-based Approach. In A. Kaban & A. Stachowicz-Stanusch (Eds.), Empowering Education: Exploring the Potential of Artificial Intelligence (pp. 65–90). ISTES BOOKS.
Jeon, I.-S., Jun, S.-J., & Song, K.-S. (2020). Teacher Training Program and Analysis of Teacher’s Demands to Strengthen Artificial Intelligence Education. Journal of The Korean Association of Information Education, 24(4), 279–289. https://doi.org/10.14352/jkaie.2020.24.4.279
Kaspersen, M. H., Bilstrup, K.-E. K., & Petersen, M. G. (2021). The Machine Learning Machine: A Tangible User Interface for Teaching Machine Learning. Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction, 1–12. https://doi.org/10.1145/3430524.3440638
Kim, S. (2021). Research Trends in Elementary and Secondary School Artificial Intelligence Education Using Topic Modeling and Problems in Technology Education. Korean Technology Education Association, 21(1), 106–124. https://doi.org/10.34138/KJTE.2021.21.1.106
Lin, P.-Y., Chai, C.-S., Jong, M. S.-Y., Dai, Y., Guo, Y., & Qin, J. (2021). Modeling the structural relationship among primary students’ motivation to learn artificial intelligence. Computers and Education: Artificial Intelligence, 2, 100006. https://doi.org/10.1016/j.caeai.2020.100006
Martínez-Comesaña, M., Rigueira-Díaz, X., Larrañaga-Janeiro, A., Martínez-Torres, J., Ocarranza-Prado, I., & Kreibel, D. (2023). Impact of artificial intelligence on assessment methods in primary and secondary education: Systematic literature review. Revista de Psicodidáctica (English Ed.), 28(2), 93–103. https://doi.org/10.1016/j.psicoe.2023.06.002
Masneri, S., Domínguez, A., Sanz, M., Zorrilla, M., Larrañaga, M., & Arruarte, A. (2023). cleAR: an interoperable architecture for multiuser AR-based school curricula. Virtual Reality, 27(3), 1813–1825. https://doi.org/10.1007/s10055-023-00764-5
Mertala, P., Fagerlund, J., & Calderon, O. (2022). Finnish 5th and 6th grade students’ prepre-instructional conceptions of artificial intelligence (AI) and their implications for AI literacy education. Computers and Education: Artificial Intelligence, 3, 100095. https://doi.org/10.1016/j.caeai.2022.100095
Miranda Veiga, F. J., & Valente de Andrade, A. M. (2021). Critical Success Factors in Accepting Technology in the Classroom. International Journal of Emerging Technologies in Learning (IJET), 16(18), 4. https://doi.org/10.3991/ijet.v16i18.23159
Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2023). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, 28(7), 8445–8501. https://doi.org/10.1007/s10639-022-11491-w
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
Ojeda-Bazaran, M.-J., Chamba-Eras, L., Coronel-Romero, E., Labanda-Jaramillo, M., Conde-Zhingre, L., Irene-Robalino, D., Fierro-Saltos, W., Orellana-Malla, A., Romero-Flores, M., Cueva-Alvarado, G., Chamba-Eras, I., & Erreyes-Pinzon, D. (2021). State of the Art of Teaching-Learning of Artificial Intelligence at Early Ages. 2021 XVI Latin American Conference on Learning Technologies (LACLO), (pp. 165–172). https://doi.org/10.1109/LACLO54177.2021.00024
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuinness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, Article n71. https://doi.org/10.1136/bmj.n71
Pardamean, B., Suparyanto, T., Cenggoro, T. W., Sudigyo, D., & Anugrahana, A. (2022). AI-Based Learning Style Prediction in Online Learning for Primary Education. IEEE Access, 10, 35725–35735. https://doi.org/10.1109/ACCESS.2022.3160177
Rodríguez-García, J. D., Moreno-León, J., Román-González, M., & Robles, G. (2021). Evaluation of an Online Intervention to Teach Artificial Intelligence with LearningML to 10-16-Year-Old Students. Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, (pp. 177–183). ACM. https://doi.org/10.1145/3408877.3432393
Russell, S., & Norvig, P. (1994). Artificial Intelligence. A Modern Approach (Third Edition). Prentice Hall.
Sabzalieva, E., & Valentini, A. (2023). ChatGPT and Artificial Intelligence in Higher Education. UNESCO.
Shi, Y., & Rao, L. (2022). Construction of STEAM Graded Teaching System Using Backpropagation Neural Network Model under Ability Orientation. Scientific Programming, 2022(1), 7792943. https://doi.org/10.1155/2022/7792943
Su, J., Ng, D. T. K., & Chu, S. K. W. (2023). Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities. Computers and Education: Artificial Intelligence, 4, 100124. https://doi.org/10.1016/J.CAEAI.2023.100124
Su, J., & Yang, W. (2022). Artificial intelligence in early childhood education: A scoping review. Computers and Education: Artificial Intelligence, 3, 100049. https://doi.org/10.1016/j.caeai.2022.100049
Sun-Ho, H., No, G., Yoon Tecnam, Sak, L., Eun-Jin, O., Choi, S.-K., & Oh-Woog, K. (2020). The Necessity of Using Dialog-Based Technology in Elementary English Education. Korean Journal of Elementary Education, 31, 173–186.
Tang, W., Hu, J., Zhang, H., Wu, P., & He, H. (2015). Kappa coefficient: a popular measure of rater agreement. Shanghai Archives of Psychiatry, 27(1), 62–67.
Vazhayil, A., Shetty, R., Bhavani, R. R., & Akshay, N. (2019). Focusing on Teacher Education to Introduce AI in Schools: Perspectives and Illustrative Findings. 2019 IEEE Tenth International Conference on Technology for Education (T4E), 71–77. https://doi.org/10.1109/T4E.2019.00021
Vicente-Yagüe-Jara, M. I., López-Martínez, O., Navarro-Navarro, V., & Cuéllar-Santiago, F. (2023). Writing, creativity, and artificial intelligence. ChatGPT in the university context. Comunicar, 31(77). https://doi.org/10.3916/C77-2023-04
Zhao, L., Wu, X., & Luo, H. (2022). Developing AI Literacy for Primary and Middle School Teachers in China: Based on a Structural Equation Modeling Analysis. Sustainability, 14(21), 14549. https://doi.org/10.3390/su142114549
Estrada-Molina, O., Ruiz Zapatero, J. L., Rodrigo Lacueva, P., Zambrano-Acosta, J. M., & Chica Chica, L. F. (2025). La inteligencia artificial en educación primaria: una revisión sistemática (2000-2024). Education in the Knowledge Society (EKS), 26, e32300. https://doi.org/10.14201/eks.32300
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