Predicción de la resiliencia docente mediante redes neuronales artificiales: influencia del burnout y del estrés por COVID-19
Resumen
Antecedentes: La resiliencia en el profesorado permite afrontar situaciones difíciles y reponerse a la adversidad existiendo diferencias de género al respecto. Asimismo, la inteligencia artificial y las técnicas asociadas a ella han resultado ser de gran utilidad para predecir variables educativas y estudiar la interconexión entre ellas tras la COVID-19. Dicho esto, el objetivo general de esta investigación fue predecir los niveles de resiliencia en las profesoras y profesores de Secundaria a través del diseño de una red neuronal artificial (RNA). Método: Se administró la Escala Breve de Afrontamiento Resiliente, el Inventario de Burnout de Maslach y el Cuestionario de Estrés frente a la COVID-19 a 401 docentes de secundaria (70.6% mujeres) de centros educativos del sureste español, con una edad media de 44.36 años (DT= 9.38). Resultados: Se hallaron diferencias en la configuración de los modelos predictivos de la resiliencia entre profesoras y profesores contribuyendo las variables independientes en diferente grado en función del género. Conclusiones: Se pone de manifiesto la utilidad de las RNA en el ámbito educativo y la necesidad de diseñar programas más ajustados.
Descargas
Citas
Abdul Aziz, I., Tajularipin, S., & Samsilah R. (2020). Models of Relationship between Emotional, Spiritual, Physical and Social Intelligence, Resilience and Burnout among High School Teachers. Universal Journal of Educational Research, 8(1A), 1-7. https://doi.org/10.13189/ujer.2020.081301.
Ainsworth, S., & Oldfield, J. (2019). Quantifying teacher resilience: Context matters. Teaching and Teacher Education. 82, 117-128. https://doi.org/10.1016/j.tate.2019.03.012
Altuntaş, S., & Genç, H. (2020). Resilience as predictor of happiness: Investigation of teacher sample. Hacettepe University Journal of Education, 35(4), 936-948. https://doi.org/10.16986/HUJE.2018046021
Arias, W. L., Huamani, J., & Ceballos, K. D. (2019). Síndrome de Burnout en profesores de escuela y universidad: un análisis psicométrico y comparativo en la ciudad de Arequipa [Burnout syndrome in school and university teachers: a psychometric and comparative analysis in the city of Arequipa]. Propósitos y Representaciones, 7(3), 72-110. http://dx.doi.org/10.20511/pyr2019.v7n3.390
Bañeres, D., Rodríguez, M. E., Guerrero-Roldán, A. E., & Karadeniz, A. (2020). An Early Warning System to Detect At-Risk Students in Online Higher Education. Applied Sciences, 10(13), 4427. http://dx.doi.org/10.3390/app10134427
Benvenuto, G., Di Genova, N., Nuzzaci, A., & Vaccarelli, A. (2021). Scala di Resilienza Professionale degli Insegnanti: prima validazione nazionale. Journal of educational , cultural and psychological studies, 23, 201-218. https://dx.doi.org/10.7358/ecps-2021-023-benv
Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century. Sustainability, 13(2), 800. https://doi.org/10.3390/su13020800
Buddhtha, S., Natasha, C., Irwansyah. E., & Budiharto, W. (2019). Building an Artificial Neural Network with Backpropagation Algorithm to Determine Teacher Engagement Based on the Indonesian Teacher Engagement Index and Presenting the Data in a Web-Based GIS. International Journal of Computational Intelligence Systems, 12(2), 1575-1584.https://doi.org/10.2991/ijcis.d.191101.003
Candeias, A., Galindo, E., Calisto, I., Borralho, L., & Reschke, K. (2021). Stress and burnout in teaching. Study in an inclusive school workplace. Health Psychology Report, 9(1), 63-75. https://doi.org/10.5114/hpr.2020.100786
Carlotto, M. S., y Câmara, S. G. (2017). Burnout syndrome profiles among teachers. Escritos de Psicología-Psychological Writings, 10(3), 159-166. https://doi.org/10.5231/psy.writ.2017.2911
Carmona, J.F., & Muñoz, C.F. (2021). Diagnosis and Intervention Program for Burnout Syndrome in Primary and Secondary Teachers at a School in Pereira. Universal Journal of Public Health, 9(2), 75 - 82. http://dx.doi.org/10.13189/ujph.2021.090206.
Chen, X., Xie, H., & Hwang, G. J. (2020). A multi-perspective study on artificial intelligence in education: Grants, conferences, journals, software tools, institutions, and researchers. Computers and Education: Artificial Intelligence, 100005.https://doi.org/10.1016/j.caeai.2020.100005
Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
Colchester, K., Hagras, H., Alghazzawi, D., & Aldabbagh, G.(2016).A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms. Journal of Artificial Intelligence and Soft Computing Research, 7(1) 47-64. https://doi.org/10.1515/jaiscr-2017-0004
Diat Prasojo, L., Habibi. A., Faiz Mohd Yaakob, M., Pratama, R, Rahimi Yusof, M., Mukminin, A., Suyanto y Hanum, F. (2020). Teachers’ burnout: A SEM analysis in an Asian context. Heliyon, 6(1), 3144. https://doi.org/10.1016/j.heliyon.2019.e03144
Dignum, V. (2021) ‘The role and challenges of education for responsible AI’. London Review of Education, 19(1), 1–11.https://doi.org/10.14324/LRE.19.1.01
Goksel, N., & Bozkurt, A. (2019). Artificial intelligence in education: Current insights and future perspectives. In Handbook of Research on Learning in the Age of Transhumanism (pp. 224-236). Pensilvania (Estados Unidos): IGI Global. https://doi.org/10.4018/978-1-5225-8431-5.ch014
Guan, M. (2020). Mental burnout of english teachers and countermeasures. Revista Argentina de Clínica Psicológica, 29(2), 244. https://doi.org/10.24205/03276716.2020.231
Guo, J., Bai, L., Yu, Z., Zhao, Z., & Wan, B. (2021). An AI-ApplicationOriented In-Class Teaching Evaluation Model by Using Statistical Modeling and Ensemble Learning. Sensors, 21(1), 241. https://doi.org/10.3390/s21010241
Hlaďo, P., Dosedlová, J., Harvánková, K., Novotný, P., Gottfried, J., Rečka, K., Petrovová, M., et al. (2020). Work Ability among Upper-Secondary School Teachers: Examining the Role of Burnout, Sense of Coherence, and Work-Related and Lifestyle Factors. International Journal of Environmental Research and Public Health, 17(24), 9185. http://dx.doi.org/10.3390/ijerph17249185
Hwang, G. J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001. https://doi.org/10.1016/j.caeai.2020.100001
Karakus, M., Ersozlu, Z., Usak, M., & Ocean, J. (2021). Self-efficacy, affective well-being, and intent-to-leave by science and mathematics teachers: A structural equation model. Journal of Baltic Science Education, 20(2),237-251. https://doi.org/10.33225/jbse/21.20.237
Kim, L.E., Jörg, V., & Klassen, R.M. (2019). A Meta-Analysis of the Effects of Teacher Personality on Teacher Effectiveness and Burnout. Educational Psycholy Review, 31, 163–195. https://doi.org/10.1007/s10648-018-9458-2
Kroupis, I., Kourtessis, T., Kouli, O., Tzetzis, G., Derri, V., & Mavrommatis, G. (2017). Job satisfaction and burnout among Greek PE teachers. A comparison of educational sectors, level and gender.(Satisfacción laboral y burnout de los profesores de la educación física en Grecia). Cultura, ciencia y deporte, 12(34), 5-14. https://doi.org/10.12800/ccd.v12i34.827
Kroupis, I., Kourtessis, T., Kouli, O., Tzetzis, G., Derri, V., & Mavrommatis, G. (2017). Job satisfaction and burnout among Greek P.E. teachers. A comparison of educational sectors, level and gender. (Satisfacción laboral y burnout de los profesores de la educación física en Grecia) [A comparison of educational sectors, level and gender (Job satisfaction and burnout of physical education teachers in Greece)]. Cultura, Ciencia y Deporte, 12(34), 5-14. https://doi.org/10.12800/ccd.v12i34.827
Liu, F., Chen, H., Xu, J., Wen, Y., & Fang, T. (2021). Exploring the Relationships between Resilience and Turnover Intention in Chinese High School Teachers: Considering the Moderating Role of Job Burnout. International Journal of Environmental Research and Public Health, 18(12), 6418. https://doi.org/10.3390/ijerph18126418
Llorca-Pellicer, M., Soto-Rubio, A., & Gil-Monte, P. R. (2021) Development of Burnout Syndrome in Non-university Teachers: Influence of Demand and Resource Variables. Frontiers in Psychology, 12, 644025. https://doi.org/10.3389/fpsyg.2021.644025
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J. H., Ogata, H., Baltes, J., Guerra, R., Li, P., & Tsai C. C. (2020) Challenges and Future Directions of Big Data and Artificial Intelligence in Education. Frontiers in Psychology, 11, 580820. https://doi.org/10.3389/fpsyg.2020.580820
Marić, N., Mandić-Rajčević, S., Maksimović, N., y Bulat, P. (2020). Factors Associated with Burnout Syndrome in Primary and Secondary School Teachers in the Republic of Srpska (Bosnia and Herzegovina). International Journal of Environmental Research and Public Health, 17(10), 3595. MDPI AG. http://dx.doi.org/10.3390/ijerph17103595
Autor (2021).
Maslach, C., & Jackson, S.E. (1986). Maslach Burnout Inventory. Palo alto, CA: Consulting Psychologists Press.
Matiz, A., Fabbro, F., Paschetto, A., Cantone, D., Paolone, A. R., & Crescentini, C. (2020). Positive Impact of Mindfulness Meditation on Mental Health of Female Teachers during the COVID-19 Outbreak in Italy. International Journal of Environmental Research and Public Health, 17(18), 6450. http://dx.doi.org/10.3390/ijerph17186450
Moret-Tatay, C., Fernández-Muñoz, J.J., Civera-Mollá, C., Navarro-Pardo, E., & Alcover-de-la-Hera, C. (2015). Propiedades psicométricas y estructura factorial del BRCS en una muestra de personas mayores españolas [Psychometric properties and factorial structure of the BRCS in a sample of Spanish elderly people]. Anales de Psicología, 31, 1030–1034.
Mota, A. I., Lopes, J., & Oliveira, C. 2021. Teachers Voices: A Qualitative Study on Burnout in the Portuguese Educational System. Education Sciences, 11(8), 392. https://doi.org/10.3390/educsci11080392
Paek, S., & Kim, N. (2021). Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education. Sustainability, 13(14), 7941. https://doi.org/10.3390/su13147941
Platsidou, M., y Daniilidou, A. (2021). Meaning in life and resilience among teachers. Journal of Positive School Psychology, 5(2), 97–109. https://doi.org/10.47602/jpsp.v5i2.259
Pokrivcakova, S. (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of Language and Cultural Education, 7(3) 135-153. https://doi.org/10.2478/jolace-2019-0025
Polat, D. D., y İskender, M. (2018). Exploring teachers’ resilience in relation to job satisfaction, burnout, organizational commitment and perception of organizational climate. International Journal of Psychology and Educational Studies, 5(3), 1-13.https://doi.org/10.17220/ijpes.2018.03.001
Reiss, M. J. (2021). The use of AI in education: Practicalities and ethical considerations. London Review of Education, 19(1), 1–14. https://doi.org/10.14324/LRE.19.1.05
Roohani, A., & Iravani, M. (2020). The Relationship Between Burnout and Self-Efficacy among Iranian Male and Female EFL Teachers. Journal of Language and Education, 6(1), 173-188. https://doi.org/10.17323/jle.2020.9793
Salanova, M., Schaufeli, W. B., Llorens, S., Peiró, J. M., & Grau, R. (2000). Desde el "burnout" al "engagement": ¿una nueva perspectiva? [From burnout to engagement: a new perspective?] Revista de Psicología del Trabajo y las Organizaciones, 16(2), 117-134.
Salmela-Aro, K., Hietajärvi, L., & Lonka, K. (2019) Work Burnout and Engagement Profiles Among Teachers. Frontiers in Psychology, 10, 2254. http://dx.doi.org/10.3389/fpsyg.2019.02254
Sánchez-Pujalte, L., Navarro, M., Etchezahar, E., y Gómez, T. (2021). Teachers’ Burnout during COVID-19 Pandemic in Spain: Trait Emotional Intelligence and Socioemotional Competencies. Sustainability, 13(13), 7259. https://doi.org/10.3390/su13137259
Schiff, D. (2021). Out of the laboratory and into the classroom: the future of artificial intelligence in education. AI & Society, 36, 331–348. https://doi.org/10.1007/s00146-020-01033-8
Seibt, R., & Kreuzfeld, S. (2021). Influence of Work-Related and Personal Characteristics on the Burnout Risk among Full- and Part-Time Teachers. International Journal of Environmental Research and Public Health, 18(4), 1535. http://dx.doi.org/10.3390/ijerph18041535
Sinclair, V. G., & Wallston, K. A. (2004). The development and psychometric evaluation of the Brief Resilient Coping Scale. Assessment, 11, 94–101.
Szempruch, J. (2018). Feeling of Professional Burnout in Teachers of Secondary Schools. The New Educational Review, 54, 219-230. https://doi.org/10.15804/tner.2018.54.4.18
Tsang, K. K., Teng, Y., Lian, Y., y Wang, L. (2021). School Management Culture, Emotional Labor, and Teacher Burnout in Mainland China. Sustainability, 13(16), 9141. http://dx.doi.org/10.3390/su13169141
Väisänen, S., Pietarinen, J., Pyhältö, K., Toom, A., & Soini, T. (2018). Student teachers’ proactive strategies for avoiding study-related burnout during teacher education. European Journal of Teacher Education, 41(3), 301-317. https://doi.org/10.1080/02619768.2018.1448777
Valentino, S., & Sosnowski, C. (2019). Emerging theory of teacher resilience: a situational analysis. English Teaching: Practice & Critique, 18(4), 492-507. https://doi.org/10.1108/ETPC-12-2018-0118
Valosek, L., Wendt, S., Link, J., Abrams, A., Hipps, J., Grant, J., Nidich, R., Loiselle, M., & Nidich, S. (2021). Meditation Effective in Reducing Teacher Burnout and Improving Resilience: A Randomized Controlled Study. Frontiers in Education, 6, 627923. http://dx.doi.org/10.3389/feduc.2021.627923
Vicente de Vera, M. I., & Gabari Gambarte, M. I. (2019). Burnout y Factores de Resiliencia en Docentes de Educación Secundaria [Burnout and Resilience Factors in Secondary School Teachers]. International Journal of Sociology of Education, 8(2), 127-152. https://doi.org/10.17583/rise.2019.3987
Yada, A., Bjorn, M. P., Savolainen, P., Kyttala, M., Aro, M., & Savolainen, H. (2021). Pre service teachers’self-efficacy in implementing inclusive practicesand resilience in Finland. Teaching and Teacher Education, 105, 103398. https://doi.org/10.1016/j.tate.2021.103398
Yang, C. (2019). Correlation between mental health, work pressure and job burnout of music teachers. Revista Argentina de Psicología Clínica, 29(2), 542. http://dx.doi.org/10.24205/03276716.2020.275
Yorulmaz, Y. İ., & Altinkurt, Y. (2018). The examination of teacher burnout in Turkey: A meta-analysis. Turkish Journal of Education, 7(1), 34-54. https://doi.org/10.19128/turje.348273
Derechos de autor 2022 Servicio de Publicaciones, Universidad de Murcia (España)
Esta obra está bajo una licencia internacional Creative Commons Atribución-CompartirIgual 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.
© Servicio de Publicaciones, Universidad de Murcia, 2024
2. Las obras se publican en la edición electrónica de la revista bajo una licencia Creative Commons Reconocimiento-CompartirIgual 4.0 Internacional (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 enviada a la revista) 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.
