Emerging Technologies in Education: Personalized and Automated Learning
Tecnologías Emergentes en Educación: Aprendizaje Personalizado y Automatizado
DOI:
https://doi.org/10.29394/Scientific.issn.2542-2987.2025.10.35.14.297-320Keywords:
emerging technologies, artificial intelligence in education, personalized learning, educational automation, pedagogical innovationAbstract
Emerging technologies such as artificial intelligence, virtual reality, and automated learning transform educational processes by offering unique opportunities to personalize education according to individual student needs. The objective was to analyze the impact of the teaching-learning process affected by the low level of application of emerging technologies in the technical industrial high school of the Jaime Roldós Aguilera Educational Unit. A mixed methodology (qualitative-quantitative) with an inductive-deductive approach was employed, applying validated surveys to 46 students and semi-structured interviews to 8 teachers and administrators. The results evidenced a strong positive correlation between the use of emerging technologies and their educational impact, with a Pearson coefficient of 0,824, indicating that 68% of the variance in academic results is explained by technological implementation. The implementation of the Moodle platform through five strategic phases and teacher training was proposed. The research concludes that the systematic integration of emerging technologies significantly improves learning personalization and generates measurable pedagogical transformations when accompanied by adequate teacher training and sustained institutional support.
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Ahmad, S., Rahmat, M., Mubarik, M., Alam, M., & Hyder, S. (2021). Artificial intelligence and its role in education. Sustainability, 13(22), 1-11, e-ISSN: 2071-1050. Retrieved from: https://doi.org/10.3390/su132212902
Akram, H., Abdelrady, A., Al-Adwan, A., & Ramzan, M. (2022). Teachers’ perceptions of technology integration in teaching-learning practices: a systematic review. Frontiers in Psychology, 13, 1-9, e-ISSN: 1664-1078. Retrieved from: https://doi.org/10.3389/fpsyg.2022.920317
Alamri, H., Watson, S., & Watson, W. (2021). Learning technology models that support personalization within blended learning environments in higher education. TechTrends, 65, 62-78, e-ISSN: 1559-7075. Retrieved from: https://doi.org/10.1007/s11528-020-00530-3
Almufarreh, A., & Arshad, M. (2023a,b). Promising emerging technologies for teaching and learning: recent developments and future challenges. Sustainability, 15(8), 1-21, e-ISSN: 2071-1050. Retrieved from: https://doi.org/10.3390/su15086917
Alvarez-Aros, E., & Bernal-Torres, C. (2021). Technological competitiveness and emerging technologies in industry 4.0 and industry 5.0. Anais da Academia Brasileira de Ciências, 93(1), 1-20, e-ISSN: 1678-2690. Retrieved from: https://doi.org/10.1590/0001-3765202120191290
Ambele, R., Kaijage, S., Dida, M., Trojer, L., & Kyando, N. (2022). A review of the development trend of personalized learning technologies and its applications. Ijasre. International Journal of Advances in Scientific. Research and Engineering, 8(11), 75-91, e-ISSN: 2454-8006. Retrieved from: https://doi.org/10.31695/IJASRE.2022.8.11.9
Amores-Valencia, A., Burgos, D., & Branch-Bedoya, J. (2022). Influence of motivation and academic performance in the use of augmented reality in education. A systematic review. Frontiers in Psychology, 13, 1-17, e-ISSN: 1664-1078. Retrieved from: https://doi.org/10.3389/fpsyg.2022.1011409
Criollo-C, S., Govea, J., Játiva, W., Pierrottet, J., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2023). Towards the integration of emerging technologies as support for the teaching and learning model in higher education. Sustainability, 15(7), 1-17, e-ISSN: 2071-1050. Retrieved from: https://doi.org/10.3390/su15076055
De Vries, P. (2022). The Ethical Dimension of Emerging Technologies in Engineering Education. Education Sciences, 12(11), 1-11, e-ISSN: 2227-7102. Retrieved from: https://doi.org/10.3390/educsci12110754
Fengchun, M., Wayne, H., Ronghuai, H., & Hui, Z. (2021). Inteligencia artificial y educación: Guía para las personas a cargo de formular políticas. ISBN: 978-92-3-300165-7. Francia: UNESCO.
Forero-Corba, W., & Negre, F. (2024a,b). 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, e-ISSN: 1390-3306. Recuperado de: https://doi.org/10.5944/ried.27.1.37491
Garlinska, M., Osial, M., Proniewska, K., & Pregowska, A. (2023). The influence of emerging technologies on distance education. Electronics, 12(7), 1-29, e-ISSN: 2079-9292. Retrieved from: https://doi.org/10.3390/electronics12071550
Gutiérrez, E. (2024). Technologies for automation of online learning and teaching, adaptation of content and personalization of the learning process. Revista de Investigación Científica Huamachuco, 1(1), 43-46, e-ISSN: 3028-9009. Retrieved from: https://doi.org/10.61709/9mkea209
Hashim, S., Omar, M., Jalil, H., & Sharef, N. (2022). Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review. International Journal of Academic Research in Progressive Education and Development, 12(1), 884-903, e-ISSN: 2226-6348. Retrieved from: https://doi.org/10.6007/ijarped/v11-i1/12230
Hernández-Sampieri, R., & Mendoza, C. (2018). Metodología de la investigación. Las rutas cuantitativa, cualitativa y mixta. ISBN: 978-1-4562-6096-5. Ciudad de México, México: Editorial McGraw-Hill Education.
Kim, S., & Park, T. (2023a,b). Understanding innovation resistance on the use of a new learning management system (LMS). Sustainability, 15(16), 1-18, e-ISSN: 2071-1050. Retrieved from: https://doi.org/10.3390/su151612627
Leahy, S., Holland, C., & Ward, F. (2019). The digital frontier: envisioning future technologies impact on the classroom. Futures, 113, 1-10, e-ISSN: 0016-3287. Retrieved from: https://doi.org/10.1016/j.futures.2019.04.009
Major, L., Francis, G., & Tsapali, M. (2021). The effectiveness of technology-supported personalised learning in low- and middle-income countries: A meta-analysis. Bjet. British Journal of Educational Technology, 52, 1935-1964, e-ISSN: 0007-1013. Retrieved from: https://doi.org/10.1111/BJET.13116
Marín-Díaz, V., Sampedro, B., & Vega, E. (2022a,b). La realidad virtual y aumentada en el aula de secundaria. Campus Virtuales, 11(1), 225-236, e-ISSN: 2255-1514. Recuperado de: https://doi.org/10.54988/cv.2022.1.1030
Melo, G., Coto, M., & Acosta, M. (2023). Educación y la Inteligencia Artificial (IA). Dominio de las Ciencias, 9(4), 242-255, e-ISSN: 2477-8818. Recuperado de: https://doi.org/10.23857/dc.v9i4.3587
Ojeda-Chimborazo, M., García-Herrera, D., Erazo-Álvarez, J., & Narváez-Zurita, C. (2020). Tecnologías emergentes: Una experiencia de formación docente. Revista Arbitrada Interdisciplinaria Koinonía, 5(1), 161-183, e-ISSN: 2542-3088. Recuperado de: http://dx.doi.org/10.35381/r.k.v5i1.777
Pellas, N., Kazanidis, I., & Palaigeorgiou, G. (2020). A systematic literature review of mixed reality environments in K-12 education. Education and Information Technologies, 25, 2481-2520, e-ISSN: 1573-7608. Retrieved from: https://doi.org/10.1007/s10639-019-10076-4
Saqr, R., Al-Somali, S., & Sarhan, M. (2024). Exploring the acceptance and user satisfaction of ai-driven e-learning platforms (blackboard, moodle, edmodo, coursera and edx): an integrated technology model. Sustainability, 16(1), 1-22, e-ISSN: 2071-1050. Retrieved from: https://doi.org/10.3390/su16010204
Selfa-Sastre, M., Pifarré, M., Cujba, A., Cutillas, L., & Falguera, E. (2022). The role of digital technologies to promote collaborative creativity in language education. Frontiers in Psychology, 13, 1-13, e-ISSN: 1664-1078. Retrieved from: https://doi.org/10.3389/fpsyg.2022.828981
UNESCO (2017). Aprendizaje personalizado. Suiza: Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura.
UNESCO (2024a,b). La inteligencia artificial en la educación. Francia: Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura.
Vivas, A., Martínez, M. (2023). Aprendizaje Automático o ‘Machinelearning’ en la Educación. Boletín de Opiniones Iberoamericanas en Educación, 5(42), 15-17. Chile: Universidad Miguel de Cervantes.
Walkington, C., & Bernacki, M. (2020a,b,c). Appraising research on personalized learning: Definitions, theoretical alignment, advancements, and future directions. Journal of Research on Technology in Education, 52(3), 235-252, e-ISSN: 1539-1523. Retrieved from: https://doi.org/10.1080/15391523.2020.1747757
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