Agencia docente e inteligencia artificial generativa en educación: análisis bibliométrico y mapeo científico (2022–2026)
DOI:
https://doi.org/10.70577/vk70zn70Palabras clave:
agencia docente; inteligencia artificial generativa; formación docente; bibliometría; mapeo científico.Resumen
La inteligencia artificial generativa ha introducido nuevas formas de asistencia, automatización y coproducción en la enseñanza, lo que ha intensificado el debate sobre la agencia docente, el juicio pedagógico y la distribución de responsabilidades entre personas y sistemas. El objetivo fue analizar la evolución, calidad de las fuentes y estructura conceptual de la producción científica que vincula agencia docente e IAG entre 2022 y 2026. Se desarrolló un análisis bibliométrico exploratorio sobre 30 publicaciones con DOI verificado. El análisis de desempeño examinó evolución temporal y concentración de fuentes; el mapeo científico se delimitó a relaciones temáticas y co-palabras, debido a la ausencia de referencias citadas homogéneas para construir redes robustas de co-citación. La interpretación se apoyó en la conceptualización ecológica de la agencia, entendida como logro temporal y relacional que articula experiencia previa, propósitos profesionales, juicio práctico y condiciones culturales, materiales y estructurales. El 80,0% del corpus se concentra en 2025-2026 y se organiza en cuatro macrotemas: agencia y juicio, formación docente, conocimiento profesional y evaluación-gobernanza. Las fuentes nucleares incluyen revistas Q1 según SJR 2024, entre ellas Teaching and Teacher Education, Assessing Writing, British Journal of Educational Technology, System, Computers and Education Open y Computers and Education: Artificial Intelligence. Se concluye que la agenda científica se desplaza desde la adopción instrumental hacia la negociación del control, la responsabilidad y los límites de delegación profesional ante la IAG.
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Referencias
Aldighrir, W. M. (2026). Development and validation of the teachers generative AI professional competence scale. Scientific Reports. https://doi.org/10.1038/s41598-026-65021-6
Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
Ayanwale, M. A., Adelana, O. P., Molefi, R. R., Adeeko, O., & Ishola, A. M. (2024). Examining artificial intelligence literacy among pre-service teachers for future classrooms. Computers and Education Open, 6, 100179. https://doi.org/10.1016/j.caeo.2024.100179
Barrot, J. S. (2026). Generative artificial intelligence for automated essay scoring: Exploring teacher agency through an ecological perspective. Assessing Writing, 67, 100990. https://doi.org/10.1016/j.asw.2025.100990
Biesta, G., Priestley, M., & Robinson, S. (2015). The role of beliefs in teacher agency. Teachers and Teaching, 21(6), 624-640. https://doi.org/10.1080/13540602.2015.1044325
Chen, Q., Tawilapakul, U., & Lin, A. M. Y. (2026). Teacherness in the age of GenAI: An ethnographic exploration of pedagogical decision-making and AI integration in English language teaching. System, 136, 103877. https://doi.org/10.1016/j.system.2025.103877
Chen, R., Lee, V. R., & G Lee, M. (2025). A cross-sectional look at teacher reactions, worries, and professional development needs related to generative AI in an urban school district. Education and Information Technologies, 30(11), 16045-16082. https://doi.org/10.1007/s10639-025-13350-w
Chen, X., & Pi, X. (2026). Assessing EFL students’ GenAI-assisted writing: Teachers’ pains, perceptions and practices. Assessing Writing, 67, 100996. https://doi.org/10.1016/j.asw.2025.100996
Chu, T., & Wang, W. (2025). Exploring EFL teachers’ epistemic agency and its influencing factors in an AI-integrated context through the double stimulation model. The Asia-Pacific Education Researcher, 34(4), 1267-1275. https://doi.org/10.1007/s40299-024-00940-4
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
Du, H., Sun, Y., Jiang, H., Islam, A. Y. M. A., & Gu, X. (2024). Exploring the effects of AI literacy in teacher learning: An empirical study. Humanities and Social Sciences Communications, 11, 559. https://doi.org/10.1057/s41599-024-03101-6
Eedelouei, S. (2026). Factors influencing language teachers’ judgements and decision-making about the use of generative AI tools: A systematic review. Teaching and Teacher Education, 171, 105333. https://doi.org/10.1016/j.tate.2025.105333
Huang, T., Wu, C., & Wu, M. (2025). Developing pre-service language teachers’ GenAI literacy: An interventional study in an English language teacher education course. Discover Artificial Intelligence, 5, 163. https://doi.org/10.1007/s44163-025-00435-1
Jia, W., & Pun, J. (2025). Exploring EMI teachers’ agency in addressing language-related challenges with ChatGPT: A multiple case study. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2025.2511061
Kahn, P., Carrigan, M., Smith, P., Murtagh, L., Liu, R., & Song, F. (2025). Teacher agency and generative artificial intelligence: Teaching in higher education as a responsive, cultural activity. Learning, Media and Technology. https://doi.org/10.1080/17439884.2025.2575993
Khodi, A., Curle, S., & Parra-Guinaldo, V. (2026). Pedagogical prompting rather than technical mastery: Generative AI use by English and English-medium instruction teachers. Frontiers in Education, 11, 1901680. https://doi.org/10.3389/feduc.2026.1901680
Kohnke, L., & Moorhouse, B. L. (2026). Avoiding de-skilling and dependency: A practical guide to using generative AI in TESOL teacher education. TESOL Quarterly. https://doi.org/10.1002/tesq.70203
Kohnke, L., Zou, D., Lai, C., & Gu, M. M. (2026). Preparing pre-service teachers for responsible generative AI use: Curriculum implications for ethics, privacy, and AI literacy. Computers and Education: Artificial Intelligence, 10, 100617. https://doi.org/10.1016/j.caeai.2026.100617
Krushinskaia, K., Elen, J., & Raes, A. (2026). Pre-service teachers’ agency during their interactions with generative AI while designing for learning – a process view on Intelligent-TPACK. Computers and Education Open, 10, 100325. https://doi.org/10.1016/j.caeo.2025.100325
Lee, S., Jeon, J., & Choe, H. (2025). Generative AI (GenAI) and pre-service teacher agency in ELT. ELT Journal, 79(2), 287-296. https://doi.org/10.1093/elt/ccaf005
Leijen, Ä., Pedaste, M., & Baucal, A. (2024). A new psychometrically validated questionnaire for assessing teacher agency in eight dimensions across pre-service and in-service teachers. Frontiers in Education, 9, 1336401. https://doi.org/10.3389/feduc.2024.1336401
Li, Z., Wang, C., & Bonk, C. J. (2026). Generative AI for teachers’ self-directed professional development: A mixed-methods study. TechTrends, 70(1), 23-38. https://doi.org/10.1007/s11528-025-01123-8
Mishra, P., Margerum-Leys, J., Trainin, G., Hill-Jackson, V., Bobley, L., Bedesem, P. L., Williams, J. A., III, & Craig, C. J. (2025). Teacher education in the age of generative artificial intelligence: Introducing the special issue. Journal of Teacher Education, 76(3), 225-229. https://doi.org/10.1177/00224871251324713
Mishra, P., Warr, M., & Islam, R. (2023). TPACK in the age of ChatGPT and Generative AI. Journal of Digital Learning in Teacher Education, 39(4), 235-251. https://doi.org/10.1080/21532974.2023.2247480
Montazeri, A., Mohammadi, S., M.Hesari, P., Ghaemi, M., Riazi, H., & Sheikhi-Mobarakeh, Z. (2023). Preliminary guideline for reporting bibliometric reviews of the biomedical literature (BIBLIO): A minimum requirements. Systematic Reviews, 12, 239. https://doi.org/10.1186/s13643-023-02410-2
Moorhouse, B. L., & Kohnke, L. (2024). The effects of generative AI on initial language teacher education: The perceptions of teacher educators. System, 122, 103290. https://doi.org/10.1016/j.system.2024.103290
Moorhouse, B. L., Yeo, M. A., & Wan, Y. (2023). Generative AI tools and assessment: Guidelines of the world’s top-ranking universities. Computers and Education Open, 5, 100151. https://doi.org/10.1016/j.caeo.2023.100151
Ó Ceallaigh, T. J., & Murphy, S. (2026). Teaching the teachers: A systematic review of GenAI-specific technological pedagogical knowledge (TPK) in teacher education. Computers and Education Open, 10, 100367. https://doi.org/10.1016/j.caeo.2026.100367
Pan, H.-L. W., & Chen, W.-H. (2026). Mapping the evolution of teacher agency research: A bibliometric review. Teaching and Teacher Education, 178, 105593. https://doi.org/10.1016/j.tate.2026.105593
Panday-Shukla, P. (2025). Exploring generative artificial intelligence in teacher education. Teaching and Teacher Education, 165, 105088. https://doi.org/10.1016/j.tate.2025.105088
Priestley, M., Biesta, G., & Robinson, S. (2015). Teacher agency: An ecological approach. Bloomsbury Academic. https://doi.org/10.5040/9781474219426
Song, Z., Qin, J., Jin, F., Cheung, W. M., & Lin, C.-H. (2025). A case study of teachers’ generative artificial intelligence integration processes and factors influencing them. Teaching and Teacher Education, 165, 105157. https://doi.org/10.1016/j.tate.2025.105157
Sperling, K., Stenberg, C. J., McGrath, C., Åkerfeldt, A., Heintz, F., & Stenliden, L. (2024). In search of artificial intelligence (AI) literacy in teacher education: A scoping review. Computers and Education Open, 6, 100169. https://doi.org/10.1016/j.caeo.2024.100169
Sun, X., & Jing, L. (2026). Growing Like Ivy: Exploring EFL teachers’ transformative agency in the GenAI context based on the double stimulation principle. International Journal of Applied Linguistics. https://doi.org/10.1111/ijal.70344
Tan, S. C., Tan, Y. Y., Teo, C. L., & Yuan, G. (2026). Teachers’ professional agency in learning with AI: A case study of a generative AI-based knowledge building learning companion for teachers. British Journal of Educational Technology, 57(4), 943-964. https://doi.org/10.1111/bjet.70013
Universidad Nacional de Educación. (2025a). Protocolo para el uso de la Inteligencia Artificial Generativa (IAGen) en la Universidad Nacional de Educación [Protocolo institucional]. https://unae.edu.ec/oferta/consejo-superior-universitario-2/
Universidad Nacional de Educación. (2025b). Resolución SO-012-No.-158-2025-CSU: Aprobación del Protocolo para el uso de la Inteligencia Artificial Generativa (IAGen) en la Universidad Nacional de Educación [Resolución del Consejo Superior Universitario]. https://unae.edu.ec/oferta/consejo-superior-universitario-2/
Universidad Nacional de Educación. (2026). Instructivo metodológico de titulación de la Carrera de Educación Básica Presencial (Código IMet_EB_2026_001) [Instructivo institucional].
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
Wang, Y., Derakhshan, A., & Ghiasvand, F. (2025). EFL teachers’ generative artificial intelligence (GenAI) literacy: A scale development and validation study. System, 133, 103791. https://doi.org/10.1016/j.system.2025.103791
Wu, W. C. V., Ting, K. Y., & Lin, P. H. (2025). The impact of generative AI tools on language teaching and learning: Investigating prospective teachers’ self-directed learning. European Journal of Teacher Education, 48(5), 987-1012. https://doi.org/10.1080/02619768.2025.2554682
Xu, Y., Zhong, J., & Han, Y. (2026). How teacher feedback literacy changed by using generative artificial intelligence (GenAI) feedback as exemplars: Case studies of English as a foreign language school teachers in China. Teaching and Teacher Education, 176, 105501. https://doi.org/10.1016/j.tate.2026.105501
Yang, H., & Markauskaite, L. (2025). Fostering language student teachers’ transformative agency for embracing GenAI: A formative intervention. Teaching and Teacher Education, 159, 104980. https://doi.org/10.1016/j.tate.2025.104980
Zaimoğlu, S., & Dağtaş, A. (2025). Teacher cognition and practices in using generative AI tools to support student engagement in EFL higher-education contexts. Behavioral Sciences, 15(9), 1202. https://doi.org/10.3390/bs15091202
Zou, S., Zuo, C., & Yang, Z. (2026). Professional agency as a psychological mechanism linking AI integration to language teacher identity. Frontiers in Psychology, 17, 1808230. https://doi.org/10.3389/fpsyg.2026.1808230
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629
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Derechos de autor 2026 Oscar Antonio Martínez Molina, Ana María Villón Tomalá, Luis Enrique Hernández Amaro, Richard Antonio Martínez Villegas (Autor/a)

Esta obra está bajo una licencia internacional Creative Commons Atribución-CompartirIgual 4.0.





