Inteligencia Artificial Agéntica y Juicio Pedagógico Docente: Hacia una Taxonomía de Competencias Futuras
Agentic Artificial Intelligence and Teacher Pedagogical Judgment: Toward a Taxonomy of Future Competencies
DOI:
https://doi.org/10.29394/Scientific.issn.2542-2987.2026.11.41.1.16-36Palabras clave:
inteligencia artificial agéntica, juicio pedagógico, competencias docentes, formación docente, revisión sistemáticaResumen
El avance de los sistemas de inteligencia artificial (IA) hacia arquitecturas agénticas capaces de planificar, ejecutar acciones secuenciales y tomar decisiones operativas en contextos educativos plantea desafíos pedagógicos que la literatura ha identificado de manera dispersa y sin marco integrador. El objetivo fue sistematizar la producción científica reciente sobre IA agéntica, juicio pedagógico docente y competencias profesionales emergentes, con el fin de construir una taxonomía de competencias futuras para la formación y el desarrollo profesional docente. Se desarrolló una revisión sistemática con enfoque cualitativo, método analítico-sintético y diseño documental-bibliográfico, organizada mediante los principios de reporte PRISMA 2020. Se consultaron Scopus, Web of Science, ERIC, ScienceDirect, SpringerLink e IEEE Xplore, con Google Scholar como complemento, entre enero de 2019 y mayo de 2026. Se incluyeron documentos académicos con identificador persistente, en español, inglés o portugués, sobre IA en educación, competencias docentes o juicio pedagógico, y se excluyeron los materiales de divulgación y los carentes de texto completo. De 1.247 registros se seleccionaron 61 fuentes primarias, sometidas a análisis temático por categorías emergentes. Los resultados caracterizan la IA agéntica en educación, identifican cuatro vectores de transformación del rol docente y documentan los riesgos pedagógicos, éticos y de privacidad asociados. A partir de ellos se construye una taxonomía de ocho competencias en los planos cognitivo-crítico, pedagógico, ético, evaluativo, decisional, socioemocional, investigativo y curricular. El corpus sugiere que el juicio pedagógico docente adquiere una función articuladora que los marcos de competencia digital vigentes no definían con tal especificidad.
Descargas
Citas
Acharya, D. B., Kuppan, K., & Divya, B. (2025). Agentic AI: Autonomous intelligence for complex goals—A comprehensive survey. IEEE Access, 13, 18912–18936. https://doi.org/10.1109/ACCESS.2025.3532853
Antonio, R. (2025). Fostering preservice science teachers' AI-TPACK competence and reflections through an AI-focused pedagogical learning course. Journal of Technology and Science Education, 15(3), 784–809. https://doi.org/10.3926/jotse.3693
Baeyaert, J. (2025). Operationalising ethical AI governance: A triadic framework for the European AI act. AI and Ethics, 6(1), Article 21. https://doi.org/10.1007/s43681-025-00882-7
Bhimavarapu, U. (2025). Digital literacy and critical thinking enhancing student perspectives on artificial intelligence. En Exploration of K-12 teaching and learning for teacher educators (pp. 107–120). IGI Global. https://doi.org/10.4018/979-8-3693-9370-3.ch005
Blonder, R., Feldman-Maggor, Y., & Rap, S. (2025). Are they ready to teach? Generative AI as a means to uncover pre-service science teachers' PCK and enhance their preparation program. Journal of Science Education and Technology, 34(6), 1301–1310. https://doi.org/10.1007/s10956-024-10180-2
Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), Article 38. https://doi.org/10.1186/s41239-023-00408-3
Chen, Y. (2025). Human oversight and governance mechanisms for generative AI in organizations [Informe]. Iowa State University. https://doi.org/10.31274/cc-20260223-24
Eager, B., Parsell, M., & Newstead, T. (2025). A human–AI co-generative framework for higher education. In S. Popenici, J. Rudolph, F. Ismail, & S. Tan (Eds.), Handbook of artificial intelligence in higher education (pp. 54–66). Edward Elgar Publishing. https://doi.org/10.4337/9781035338764.00010
Ferster, B. (2022). Intelligent tutoring systems. En Intelligent tutoring systems. Routledge. https://doi.org/10.4324/9781138609877-ree6-1
Forde, C., & McMahon, M. (2019a). Issues of teacher expertise and teacher quality. En Teacher quality, professional learning and policy (pp. 31–54). Palgrave Macmillan. https://doi.org/10.1057/978-1-137-53654-9_2
Forde, C., & McMahon, M. (2019b). Teacher professional learning: Building expertise over a teaching career. En Teacher quality, professional learning and policy (pp. 139–166). Palgrave Macmillan. https://doi.org/10.1057/978-1-137-53654-9_6
Ghomi, M., & Redecker, C. (2019). Digital competence of educators (DigCompEdu): Development and evaluation of a self-assessment instrument for teachers' digital competence. En Proceedings of the 11th International Conference on Computer Supported Education (pp. 541–548). SCITEPRESS. https://doi.org/10.5220/0007679005410548
Godwin-Jones, R. (2025). Language teacher preparation for an AI world: A human ecological perspective. En Rethinking language education in the age of generative AI (pp. 29–43). Routledge. https://doi.org/10.4324/9781003426929-4
Goyal, E. (2025). Agentic AI: Advancing autonomous decision-making and adaptive intelligence in complex systems. International Journal of Science and Research, 14(8), 100–105. https://doi.org/10.21275/sr25713112356
Grant, M. J., & Booth, A. (2009). A typology of reviews: An analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26(2), 91–108. https://doi.org/10.1111/j.1471-1842.2009.00848.x
Grant, A., Hann, T., Godwin, R., Shackelford, D., & Ames, T. (2020). A framework for graduated teacher autonomy: Linking teacher proficiency with autonomy. The Educational Forum, 84(2), 100–113. https://doi.org/10.1080/00131725.2020.1700324
Hernández-Sampieri, R., & Mendoza, C. P. (2018). Metodología de la investigación: Las rutas cuantitativa, cualitativa y mixta. McGraw-Hill Education.
Holm, S. (2023). Algorithmic legitimacy in clinical decision-making. Ethics and Information Technology, 25(3), Article 35. https://doi.org/10.1007/s10676-023-09709-7
Huang, X., & Zhang, S. (2025). Teachers' generative AI-facilitated informal learning: A scope review. European Journal of Teacher Education, 48(5), 1077–1102. https://doi.org/10.1080/02619768.2025.2571920
Judijanto, L. (2025). Beyond access: Cultural, ethical, and infrastructural challenges of AI in marginalised education contexts. European Journal of Contemporary Education and E-Learning, 3(6), 83–98. https://doi.org/10.59324/ejceel.2025.3(6).07
Kiosoglous, C. (2025). Building digital equity through curriculum development: Navigating AI, ethics, and critical thinking in the age of information. En Digital Equity and Literacy. IntechOpen. https://doi.org/10.5772/intechopen.1011973
Kiser, R. (2023a). Expertise, motivation, and wisdom. En Professional judgment for lawyers (pp. 293–322). Edward Elgar Publishing. https://doi.org/10.4337/9781035314812.00015
Kiser, R. (2023b). Individual decision-making expertise. En Professional judgment for lawyers (pp. 358–393). Edward Elgar Publishing. https://doi.org/10.4337/9781035314812.00017
Kohnke, L. (2024). Enhancing teacher professional development with AI. En Optimizing digital competence through microlearning (pp. 55–66). Springer. https://doi.org/10.1007/978-981-97-8839-2_6
Kshetri, N. (2025). Revolutionizing higher education: The impact of artificial intelligence agents and agentic artificial intelligence on teaching and operations. IT Professional, 27(2), 12–16. https://doi.org/10.1109/mitp.2025.3550697
Langer, M., Baum, K., & Schlicker, N. (2024). Effective human oversight of AI-based systems: A signal detection perspective on the detection of inaccurate and unfair outputs. Minds and Machines, 35(1), Article 1. https://doi.org/10.1007/s11023-024-09701-0
Larsson, S. (2020). On the governance of artificial intelligence through ethics guidelines. Asian Journal of Law and Society, 7(3), 437–451. https://doi.org/10.1017/als.2020.19
Lawrence, L., Echeverria, V., Yang, K., Aleven, V., & Rummel, N. (2023). How teachers conceptualise shared control with an AI co-orchestration tool: A multiyear teacher-centred design process. British Journal of Educational Technology, 55(3), 823–844. https://doi.org/10.1111/bjet.13372
Lee, H., & Bryan, L. M. (2025). Integrating AI in teacher education: Exploring the impact on preservice teacher competencies. Professional Development in Education, 51(3), 478–494. https://doi.org/10.1080/19415257.2025.2490000
Liu, J., & Peng, L. (2025). The change and challenge of teacher-student relationship in the era of artificial intelligence: Teaching interaction and emotional connection. Journal of Contemporary Educational Research, 9(6), 87–93. https://doi.org/10.26689/jcer.v9i6.10896
Mazilov, V. A., & Slepko, Y. N. (2024). Psychological analysis of competencies in the structure of teacher professional training. Integration of Education, 28(4), 514–532. https://doi.org/10.15507/1991-9468.117.028.202404.514-532
Mökander, J., Morley, J., Taddeo, M., & Floridi, L. (2021). Ethics-based auditing of automated decision-making systems: Nature, scope, and limitations. Science and Engineering Ethics, 27(4), Article 44. https://doi.org/10.1007/s11948-021-00319-4
Momdjian, L., Manegre, M., & Gutiérrez-Colón, M. (2024). Assessing and bridging the digital competence gap: A comparative study of Lebanese student teachers and in-service teachers using the DigCompEdu framework. Discover Education, 3(1), Article 198. https://doi.org/10.1007/s44217-024-00308-2
Moorhouse, B. L., & Kohnke, L. (2023). The effects of generative AI on initial language teacher education: The perspectives of teacher educators [Preimpresión]. SSRN. https://doi.org/10.2139/ssrn.4532479
Moreno, E., Hidalgo, J., & Risueño, J. J. (2025). Evaluación de la competencia digital en futuros docentes: Un análisis basado en el marco europeo DigCompEdu. European Public & Social Innovation Review, 10, 1–18. https://doi.org/10.31637/epsir-2025-2450
Mukherjee, A. (2023). Algorithmic decision making. En AI and ethics(pp. 3-1–3-20). IOP Publishing. https://doi.org/10.1088/978-0-7503-6116-3ch3
Nyaaba, M., & Zhai, X. (2024). Generative AI professional development needs for teacher educators. Journal of AI, 8(1), 1–13. https://doi.org/10.61969/jai.1385915
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Palsa, L., & Mertala, P. (2019). Multiliteracies in local curricula: Conceptual contextualizations of transversal competence in the Finnish curricular framework. Nordic Journal of Studies in Educational Policy, 5(2), 114–126. https://doi.org/10.1080/20020317.2019.1635845
Panezi, A. (2025). Requirements of high-risk AI systems: AI Act. Article 14. Human oversight [Preimpresión]. SSRN. https://doi.org/10.2139/ssrn.5131229
Passi, S. (2025). Agentic AI has a human oversight problem [Preimpresión]. SSRN. https://doi.org/10.2139/ssrn.5529058
Puja, T., Digar, S. F., Anjana, B., & Rakhi, T. (2025). AI in classrooms: Impact on teacher identity and autonomy. i-manager's Journal on School Educational Technology, 20(4), 39. https://doi.org/10.26634/jsch.20.4.21964
Radtke-Bederode, I., & Meireles-Ribeiro, L. O. (2025). Plataformización educativa con IA generativa: Impactos en la autonomía docente. Alteridad, 20(2), 178–189. https://doi.org/10.17163/alt.v20n2.2025.02
Sharma, A., & Sharifi, S. (2025). Closing the feedback loop: AI-supported systems for literacy, equity, and longitudinal learning in higher education. In ICERI2025 Proceedings (pp. 5697–5706). IATED. https://doi.org/10.21125/iceri.2025.1576
Shi, L. (2025). Promoting the workforce's AI competence development: A national AI policy perspective. En Proceedings of the 2025 AERA Annual Meeting. AERA. https://doi.org/10.3102/2185132
Somu, B. (2025). Leveraging agentic artificial intelligence capabilities to automate cognitive decision-making tasks across financial service chains. En The future of financial IT: Agentic artificial intelligence and intelligent infrastructure in modern banking (pp. 26–37). Deep Science Publishing. https://doi.org/10.70593/978-93-49910-62-1_3
Song, Y., Du, J., & Zheng, Q. (2025). Automatic item generation for educational assessments: A systematic literature review. Interactive Learning Environments, 33(9), 5386–5405. https://doi.org/10.1080/10494820.2025.2482588
Sun, H. (2025). Teacher agency in response to the emergence of generative AI: A scaffolded writing project within the multiliteracies framework. En Generative AI technologies, multiliteracies, and language education (pp. 78–101). Routledge. https://doi.org/10.4324/9781003531685-5
Trevisan, O. (2025). Digital competence and teacher education: Teacher identity, tensions and agency. En Reimagining teacher digital competence (pp. 27–45). Edward Elgar Publishing. https://doi.org/10.4337/9781035337514.00009
UNESCO (2021). AI and education: Guidance for policy-makers. UNESDOC Digital Library.
Valderrey, M. D., & Echeverría, Á. Y. (2024). Aplicaciones éticas de autonomía cognitiva con respecto a la inteligencia artificial en la educación universitaria: Ethical applications of cognitive autonomy regarding artificial intelligence in university education. Revista Scientific, 9(33), 382–403. https://doi.org/10.29394/Scientific.issn.2542-2987.2024.9.33.18.382-403
Villegas-Ch, W., Buenano-Fernandez, D., Maldonado, A., & Mera-Navarrete, A. (2025). Adaptive intelligent tutoring systems for STEM education: Analysis of the learning impact and effectiveness of personalized feedback. Smart Learning Environments, 12(1), Article 41. https://doi.org/10.1186/s40561-025-00389-y
Wang, D., & Zhang, Q. (2025). Beyond technical competencies: A critical analysis of global research on language teacher AI literacy. Proceedings of the International CALL Research Conference, 2025, 167–171. https://doi.org/10.29140/97817637116240-21
Wolf, A. (2025). Algorithmic fairness and educational justice. Educational Theory, 75(4), 661–681. https://doi.org/10.1111/edth.70029
Xu, G., Yu, A., Gao, A., & Trainin, G. (2025). Developing an AI-TPACK framework: Exploring the mediating role of AI attitudes in pre-service TCSL teachers' self-efficacy and AI-TPACK. Education and Information Technologies, 30(15), 22471–22495. https://doi.org/10.1007/s10639-025-13630-5
Ye, S. (2025). Construction and application path of core competence framework for vocational undergraduate tourism management majors driven by artificial intelligence: A qualitative study based on grounded theory. In 2025 International Conference on Educational Technology Management (ICETM) (pp. 501–506). IEEE. https://doi.org/10.1109/icetm67477.2025.11413599
Ye, W., & Wang, J. (2024). Teacher ethical regulation policies and teacher autonomy in China. Educational Studies, 52(1), 37–56. https://doi.org/10.1080/03055698.2024.2424540
Zary, N. (2025). AI literacy framework (ALiF): A comprehensive approach to developing AI competencies in educational and healthcare settings [Preimpresión]. Preprints.org. https://doi.org/10.20944/preprints202503.1188.v1
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2026 INDTEC, C.A.
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
El contenido de las revistas de este sitio, están bajo una Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional.
