Diseño y validación de un instrumento para evaluar el liderazgo transformacional y directivo en el uso responsable de la inteligencia artificial en centros educativos
Agencias de apoyo
- Este estudio ha recibido financiación del Programa Estatal de Investigación y Desarrollo Experimental, en el marco del Plan Estatal de Investigación Científica, Técnica y de Innovación 2024-2027 (Proyectos de Generación de Conocimiento 2024). Ministerio de Ciencia, Innovación y Universidades. Número de referencia: PID2024-155949OB-I00.
Resumen
A medida que las herramientas de Inteligencia Artificial (IA) y de Inteligencia Artificial Generativa (IA-Gen) se consolidan como elementos centrales en la educación, el liderazgo escolar efectivo se vuelve esencial para garantizar una integración responsable y ética. Este estudio desarrolla y valida un instrumento psicométrico destinado a evaluar las percepciones del profesorado sobre el liderazgo de sus equipos directivos en la adopción de la IA y la IA-Gen, fundamentado en las teorías del liderazgo transformacional y ético. El instrumento contempla cuatro dimensiones clave (Liderazgo empoderado, Orientación, Precaución y Colaboración-Cultura) y fue aplicado a una muestra de 470 docentes en ejercicio en España, cuyos datos fueron analizados mediante análisis factorial exploratorio y confirmatorio, revelando una estructura robusta de tres factores con alta fiabilidad (consistencia interna) y un adecuado ajuste del modelo. La validez convergente y discriminante confirmó la solidez psicométrica del instrumento, cuyas aplicaciones prácticas incluyen diagnosticar la preparación del liderazgo para la transformación digital, identificar necesidades de desarrollo profesional y orientar políticas de integración de la IA en los centros educativos. Asimismo, el estudio aporta al marco teórico del liderazgo educativo en entornos potenciados por la IA, destacando que la adopción exitosa no depende únicamente del acceso a la tecnología, sino de un liderazgo visionario, de apoyo y con fundamentos éticos.
Descargas
-
Resumen3
-
PDF 0
Citas
Adams, D. (2018). Mastering theories of educational leadership and management. University of Malaya Press.
Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101. https://doi.org/10.3390/su14031101
Bandalos, D. L., & Finney, S. J. (2018). Factor analysis: Exploratory and confirmatory. In The reviewer’s guide to quantitative methods in the social sciences (pp. 98-122). Routledge.
Bass, B. M. (1990). From transactional to transformational leadership: Learning to share the vision. Organizational dynamics, 18(3), 19-31. https://doi.org/10.1016/0090-2616(90)90061-S
Bernacki, M. L., Greene, J. A., & Crompton, H. (2020). Mobile technology, learning, and achievement: Advances in understanding and measuring the role of mobile technology in education. Contemporary Educational Psychology, 60, 101827. https://doi.org/10.1016/j.cedpsych.2019.101827
Blasé, J., & Blasé, J. (1997). The micropolitical orientation of facilitative school principals and its effects on teachers’ sense of empowerment. Journal of Educational Administration, 35(2), 138–164. https://doi.org/10.1108/09578239710161777
Blossing, U., & Liljenberg, M. (2019). School leaders’ relational and management work orientation. International Journal of Educational Management, 33(2), 276-286. https://doi.org/10.1108/IJEM-07-2017-0185
Bollen, K. A. (1989). Structural equations with latent variables (Vol. 210). John Wiley & Sons.
Bronkhorst, P. V., & Becker, J. (2024). Use of artificial intelligence in leadership competency development and selection: An empirical study. Consulting Psychology Journal, 1-27. https://doi.org/10.1037/cpb0000288
Brown, M. E., & Treviño, L. K. (2006). Ethical leadership: A review and future directions. The leadership quarterly, 17(6), 595-616. https://doi.org/10.1016/j.leaqua.2006.10.004
Bryant, J., Heitz, C., Sanghvi, S. and Wagle, D. (2020). How artificial intelligence will impact K-12 teachers. Available at: https://www.mckinsey.com/industries/social-sector/our-insights/howartificial-intelligence-will-impact-k-12-teachers (accessed 03 june 2025).
Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge.
Cattell, R. B. (1966). The screen test for the number of factors. Multivariate behavioral research, 1(2), 245-276. https://doi.org/10.1207/s15327906mbr0102_10
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
Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (Vol. 2). Ankara: Pegem Akademi.
Daugherty, Mentzer, Lybrook, & Little-Wiles. (2013). Philosophical perspectives on technology leadership. In Technology integration and foundations for effective leadership (pp. 42–56).
Deal, T. E., & Peterson, K. D. (2009). Shaping school culture: Pitfalls, paradoxes, and promises. Jossey-Bass.
Dou, D., Devos, G., & Valcke, M. (2017). The relationships between school autonomy gap, principal leadership, teachers’ job satisfaction and organizational commitment. Educational Management Administration & Leadership, 45(6), 959-977. https://doi.org/10.1177/1741143216653975
Ehrich, L. C., Harris, J., Klenowski, V., Smeed, J., & Spina, N. (2015). The centrality of ethical leadership. Journal of Educational Administration, 53(2), 197-214. https://doi.org/10.1108/JEA-10-2013-0110
Ferrando, P. J., & Anguiano-Carrasco, C. (2010). El análisis factorial como técnica de investigación en psicología. Papeles del psicólogo, 31(1), 18-33.
Forero, C. G., Maydeu-Olivares, A., & Gallardo-Pujol, D. (2009). Factor analysis with ordinal indicators: A Monte Carlo study comparing DWLS and ULS estimation. Structural equation modeling, 16(4), 625-641. https://doi.org/10.1080/10705510903203573
Galindo-Domínguez, H., Delgado, N., Campo, L., & Losada, D. (2024). Relationship between teachers’ digital competence and attitudes towards artificial intelligence in education. International Journal of Educational Research, 126, 102381. https://doi.org/10.1016/j.ijer.2024.102381
Ghamrawi, N., Shal, T., & Ghamrawi, N. A. (2024). Exploring the impact of AI on teacher leadership: regressing or expanding?. Education and Information Technologies, 29(7), 8415-8433. https://doi.org/10.1007/s10639-023-12174-w
Guardiola, M. A. (2024, June). Educational leadership and the impact of AI in the post-Covid era in Catalonia. In Conference Proceedings. The Future of Education 2024.
Guillén Gámez, F., Tomczyk, Ł., Colomo-Magaña, E., & Mascia, M. L. (2024). Digital competence of Higher Education teachers in research work: validation of an explanatory and confirmatory model. Journal Of E-Learning And Knowledge Society, 20(3), 1-12. https://doi.org/10.20368/1971-8829/1135963
Guillen-Gamez, F., Mayorga-Fernández, M. J., & Contreras-Rosado, J. A. (2021). Validity and reliability of an instrument to evaluate the digital competence of teachers in relation to online tutorials in the stages of Early Childhood Education and Primary Education. Revista De Educación a Distancia (RED), 21(67), 1-20. https://doi.org/10.6018/red.474981
Gümüş, M. M., & Kukul, V. (2023). Developing a digital competence scale for teachers: validity and reliability study. Education and Information Technologies, 28(3), 2747-2765. https://doi.org/10.1007/s10639-022-11213-2
Gürfidan, H., & Koç, M. (2016). The impact of school culture, technology leadership, and support services on teachers’ technology integration: A structural equation modeling. Education and Science, 41(188), 99-116. https://doi.org/10.15390/EB.2016.6722
Gurr, D., & Drysdale, L. (2020). Leadership for challenging times. International Studies in Educational Administration, 48(1), 24–30.
Gurr, D., Longmuir, F., & Reed, C. (2021). Creating successful and unique schools: Leadership, context and systems thinking perspectives. Journal of Educational Administration, 59(1), 59-76. https://doi.org/10.1108/JEA-02-2020-0045
Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. In J.F. Hair Jr., W.C. Black, B.J. babin, & R.E. Anderson (Eds.), Multivariate data analysis: a global perspective (pp. 785-785). Prentice Hall.
Heinzl, A., Buxmann, P., Wendt, O., & Weitzel, T. (Eds.). (2011). Theory-Guided Modeling and Empiricism in Information Systems Research. Springer Science & Business Media.
Hernández, P. A., & Esquivel, G. H. (2024). El Impacto de la Inteligencia Artificial en el Liderazgo Tecnológico 4.0. Estudios Y Perspectivas Revista Científica Y Académica, 4(2), 2009-2031. https://doi.org/10.61384/r.c.a..v4i2.349
Herold, B. (2019). Forty percent of elementary school teachers’ work could be automated by 2030, McKinsey Global Institute Predicts. Education Week.
Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure 17 analysis: Conventional criteria versus new alternatives. Structural Equation 18 Modeling: A Multidisciplinary Journal, 6(1), 1-55.
Igbokwe, I. C. (2024). Artificial Intelligence in Educational Leadership: Risks and Responsibilities. European Journal of Arts, Humanities and Social Sciences, 1(6), 3-10. https://doi.org/10.59324/ejahss.2024.1(6).01
Iqbal, Q., & Piwowar-Sulej, K. (2022). Sustainable leadership in higher education institutions: social innovation as a mechanism. International Journal of Sustainability in Higher Education, 23(8), 1-20. https://doi.org/10.1108/IJSHE-04-2021-0162
ISTE. (2018). ISTE Standards for Education Leaders. Retrieved from https://www.iste.org/standards/for-education-leaders. Accessed 06 june 2025.
Jensen, U. T., Andersen, L. B., Bro, L. L., Bøllingtoft, A., Eriksen, T. L. M., Holten, A. L., ... & Würtz, A. (2019). Conceptualizing and measuring transformational and transactional leadership. Administration & Society, 51(1), 3-33. https://doi.org/10.1177/0095399716667157
Joo, B. K., & Jo, S. J. (2017). The effects of perceived authentic leadership and core self-evaluations on organizational citizenship behavior: The role of psychological empowerment as a partial mediator. Leadership & Organization Development Journal, 38(3), 463-481. https://doi.org/10.1108/LODJ-11-2015-0254
Kafa, A. (2025). Exploring integration aspects of school leadership in the context of digitalization and artificial intelligence. International Journal of Educational Management, 39(8), 98-115. https://doi.org/10.1108/IJEM-11-2024-0703
Karsono, B., Suraji, R., & Sastrodiharjo, I. (2022). The Influence of Leadership Spirituality to Improving the Quality of Higher Education in Indonesia. International Journal of Social Sciences and Humanities Invention, 9(01), 6832-6841. http://dx.doi.org/10.18535/ijsshi/v9i02.06
Khan, F. (2025). Transformational leadership and teacher work performance: Mediating effect of job autonomy and trust in school principal–insights from senior secondary school data in India. Educational Management Administration & Leadership, 53(2), 318-338. https://doi.org/10.1177/17411432231172359
Kline, R. B. (1998). Principles and practice of structural equation modeling. Guilford Press.
Kokkonos, A., Travlos, A., Antonopoulou, P., & Korre, M. P. (2025). Questionnaire for digital technologies and leadership practices: the validity and reliability study. Int J Eval & Res Educ, 14(1), 133-145. http://doi.org/10.11591/ijere.v14i1.29885
Leo, U. (2015). Professional norms guiding school principals’ pedagogical leadership. International Journal of Educational Management, 29(4), 461-476. https://doi.org/10.1108/IJEM-08-2014-0121
Lloret-Segura, S., Ferreres-Traver, A., Hernández-Baeza, A., & Tomás-Marco, I. (2014). El análisis factorial exploratorio de los ítems: una guía práctica, revisada y actualizada. Anales de psicología/annals of psychology, 30(3), 1151-1169. https://doi.org/10.6018/analesps.30.3.199361
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological methods, 1(2), 130-149.
Maddula, S. S. (2018). The impact of AI and reciprocal symmetry on organizational culture and leadership in the digital economy. Engineering International, 6(2), 201-210. https://dx.doi.org/10.18034/ei.v6i2.703
Meroño, L., Calderón Luquin, A., Arias Estero, J. L., & Méndez Giménez, A. (2018). Diseño y validación del cuestionario de percepción del profesorado de Educación Primaria sobre el aprendizaje del alumnado basado en competencias (# ICOMpri2). Revista Complutense de Educación, 29 (1), 215-235. http://dx.doi.org/10.5209/RCED.52200
Mulaik, S. A. (2018). Fundamentals of common factor analysis. The Wiley handbook of psychometric testing: A multidisciplinary reference on survey, scale and test development, 209-251. https://doi.org/10.1002/9781118489772.ch8
Muthén, B., & Kaplan, D. (1985). A comparison of some methodologies for the factor analysis of non‐normal Likert variables. British journal of mathematical and statistical psychology, 38(2), 171-189. https://doi.org/10.1111/j.2044-8317.1985.tb00832.x
Mvududu, N. H., & Sink, C. A. (2013). Factor analysis in counseling research and practice. Counseling Outcome Research and Evaluation, 4(2), 75-98. https://doi.org/10.1177/2150137813494766
Nunnally, J., & Bernstein, I. (1994). Psychometric theory. New York: McGraw-Hill.
Nwakoby, C. S. (2025). Leadership In Educational Management. UNIZIK Journal of Educational Research and Policy Studies, 19(1), 175-186.
Salendab, F. A., & Dapitan, Y. C. (2021). Performance of Private Higher Education Institutions and the School Heads’ Supervision in South Central Min-danao. Psychology and Education, 58(3), 3980-3997. http://dx.doi.org/10.17762/pae.v58i3.4603
Sencan, H. (2005). Sosyal ve Davranissal Olçumlerde Guvenilirlik ve Gecerlilik [Validity and reliability in social and behavioral measures]. Seçkin Yayı ncılık.
Shaffer, B. T., Cohen, M. S., Bigelow, D. C., & Ruckenstein, M. J. (2010). Validation of a disease‐specific quality‐of‐life instrument for acoustic neuroma: the Penn Acoustic Neuroma Quality‐of‐Life scale. The Laryngoscope, 120(8), 1646-1654. https://doi.org/10.1002/lary.20988
Short, P. M. (1998). Empowering leadership. Contemporary Education, 69(2), 70-72.
Soriano-Alcantara, J. M., Guillén-Gámez, F. D., & Ruiz-Palmero, J. (2024). Exploring digital competencies: validation and reliability of an instrument for the educational community and for all educational stages. Technology, Knowledge and Learning, 1-20. https://doi.org/10.1007/s10758-024-09741-6
Stanescu, D. F., Zbuchea, A., & Pinzaru, F. (2021). Transformational leadership and innovative work behaviour: the mediating role of psychological empowerment. Kybernetes, 50(5), 1041-1057. https://doi.org/10.1108/K-07-2019-0491
Starratt, R. J. (2004). Ethical leadership. John Wiley & Sons.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics. Pearson Education.
Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial intelligence in education: AIEd for personalised learning pathways. Electronic Journal of e-Learning, 20(5), 639-653.
Tarhini, A., Teo, T., & Tarhini, T. (2016). A cross-cultural validity of the E-learning Acceptance Measure (ElAM) in Lebanon and England: A confirmatory factor analysis. Education and Information Technologies, 21(5), 1269-1282. https://doi.org/10.1007/s10639-015-9381-9
Töre, E., & Uzun, B. (2024). The Effect of Empowering Leadership Characteristics of School Principals According to Teachers' Perceptions on Teachers' Psychological Ownership and Work Engagement. Participatory Educational Research, 11(3), 165-183. https://doi.org/10.17275/per.24.40.11.3
Watkins, M. W. (2021). A step-by-step guide to exploratory factor analysis with SPSS. Routledge.
West, R. F., Meserve, R. J., & Stanovich, K. E. (2012). Cognitive sophistication does not attenuate the bias blind spot. Journal of Personality and Social Psychology, 103(3), 506–519. https://doi.org/10.1037/a0028857
Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The counseling psychologist, 34(6), 806-838. https://doi.org/10.1177/0011000006288127
Woyo, E., Rukanda, G. D., & Nyamapanda, Z. (2020). ICT policy implementation in higher education institutions in Namibia: A survey of students’ perceptions. Education and Information Technologies, 25(5), 3705-3722. https://doi.org/10.1007/s10639-020-10118-2
Yuting, Z., Adams, D., & Lee, K. C. S. (2022). The relationship between technology leadership and teacher ICT competency in higher education. Education and Information Technologies, 27(7), 10285-10307. https://doi.org/10.1007/s10639-022-11037-0
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0
Zhang, S., Bowers, A. J., & Mao, Y. (2021). Authentic leadership and teachers’ voice behaviour: The mediating role of psychological empowerment and moderating role of interpersonal trust. Educational Management Administration & Leadership, 49(5), 768-785. https://doi.org/10.1177/1741143220915925
Derechos de autor 2025 Revista de Educación a Distancia (RED)

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Las obras que se publican en esta revista están sujetas a los siguientes términos:
1. El Servicio de Publicaciones de la Universidad de Murcia (la editorial) conserva los derechos patrimoniales (copyright) de las obras publicadas, y favorece y permite la reutilización de las mismas bajo la licencia de uso indicada en el punto 2.
2. Las obras se publican en la edición electrónica de la revista bajo una licencia Creative Commons Reconocimiento-NoComercial-SinObraDerivada 3.0 España (texto legal). Se pueden copiar, usar, difundir, transmitir y exponer públicamente, siempre que: i) se cite la autoría y la fuente original de su publicación (revista, editorial y URL de la obra); ii) no se usen para fines comerciales; iii) se mencione la existencia y especificaciones de esta licencia de uso.
3. Condiciones de auto-archivo. Se permite y se anima a los autores a difundir electrónicamente las versiones pre-print (versión antes de ser evaluada) y/o post-print (versión evaluada y aceptada para su publicación) de sus obras antes de su publicación, ya que favorece su circulación y difusión más temprana y con ello un posible aumento en su citación y alcance entre la comunidad académica. Color RoMEO: verde.







