Integration of information and communication technologies (ICT) and artificial intelligence (AI) in teacher training
DOI:
https://doi.org/10.36825/RITI.13.29.006Keywords:
Teacher Training, Artificial Intelligence, Digital Competencies, Higher Education, Educational TechnologyAbstract
This study examines the integration of Information and Communication Technologies (ICT) and Artificial Intelligence (AI) in teacher training at the University of Guayaquil, Ecuador. The research, involving 250 students and 100 teachers from various pedagogical careers, employed a quantitative approach with analysis of variance and multiple regression. Results reveal significant differences in digital competencies and attitudes towards AI among careers, with experimental sciences showing higher levels. Students exhibited greater digital competence and more positive attitudes towards AI than teachers. Digital competencies, attitudes towards AI, and previous experience with technology were significant predictors of willingness to integrate ICT and AI into teaching practice. The study concludes that a differentiated approach in technological training is necessary for different pedagogical specialties and generations of educators, providing an empirical basis for designing teacher training programs and educational policies in the digital era.
References
Mishra, P., Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108 (6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu. Publications Office of the European Union. https://publications.jrc.ec.europa.eu/repository/handle/JRC107466
Tondeur, J., van Braak, J., Ertmer, P. A., Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers' pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65 (3), 555-575. https://doi.org/10.1007/s11423-016-9481-2
Holmes, W., Bialik, M., Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
Zhu, M., Sari, A., Lee, M. M. (2020). A systematic review of research methods and topics of the empirical MOOC literature (2014–2016). The Internet and Higher Education, 37, 31-39. https://doi.org/10.1016/j.iheduc.2018.01.002
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, 1-27. https://doi.org/10.1186/s41239-019-0171-0
Puentedura, R. (2006). Transformation, technology, and education. Hippasus. http://hippasus.com/resources/tte/
Hamilton, E. R., Rosenberg, J. M., Akcaoglu, M. (2016). The substitution augmentation modification redefinition (SAMR) model: A critical review and suggestions for its use. TechTrends, 60 (5), 433-441. https://doi.org/10.1007/s11528-016-0091-y
Voogt, J., Fisser, P., Pareja Roblin, N., Tondeur, J., van Braak, J. (2013). Technological pedagogical content knowledge–a review of the literature. Journal of Computer Assisted Learning, 29 (2), 109-121. https://doi.org/10.1111/j.1365-2729.2012.00487.x
Ertmer, P. A., Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42 (3), 255-284. https://doi.org/10.1080/15391523.2010.10782551
Soomro, K. A., Kale, U., Curtis, R., Akcaoglu, M., Bernstein, M. (2020). Digital divide among higher education faculty. International Journal of Educational Technology in Higher Education, 17 (21), 1-16. https://doi.org/10.1186/s41239-020-00191-5
Selwyn, N. (2019). What's the problem with learning analytics? Journal of Learning Analytics, 6 (3), 11-19. https://doi.org/10.18608/jla.2019.63.3
Williamson, B., Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45 (3), 223-235. https://doi.org/10.1080/17439884.2020.1798995
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, 1-5. https://doi.org/10.1016/j.caeai.2020.100001
Bartolomé, A., Castañeda, L., Adell, J. (2018). Personalisation in educational technology: The absence of underlying pedagogies. International Journal of Educational Technology in Higher Education, 15 (1), 14. https://doi.org/10.1186/s41239-018-0095-0
Billingsley, G., Smith, S., Smith, S., Meritt, J. (2019). A systematic literature review of using immersive virtual reality technology in teacher education. Journal of Interactive Learning Research, 30 (1), 65-90. https://www.learntechlib.org/primary/p/176261/
Ruiz Muñoz, G. F., Yépez González, D. A., Romero Amores, N. V., & Cali Proaño, Ángela F. (2024). Augmented reality’s impact on STEM learning. Salud, Ciencia Y Tecnología, 4, 1-9. https://doi.org/10.56294/saludcyt20241202
Mangaroska, K., Giannakos, M. N. (2019). Learning analytics for learning design: A systematic literature review of analytics-driven design to enhance learning. IEEE Transactions on Learning Technologies, 12 (4), 516-534. https://doi.org/10.1109/TLT.2018.2868673
Kitto, K., Shum, S. B., & Gibson, A. (2018). Embracing imperfection in learning analytics. 8th International Conference on Learning Analytics and Knowledge. Sydney New South Wales Australia. https://doi.org/10.1145/3170358.3170413
Hodges, C., Moore, S., Lockee, B., Trust, T., Bond, A. (2020). The difference between emergency remote teaching and online learning. Educause Review. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning
Trust, T., Whalen, J. (2020). Should teachers be trained in emergency remote teaching? Lessons learned from the COVID-19 pandemic. Journal of Technology and Teacher Education, 28 (2), 189-199. https://www.learntechlib.org/primary/p/215995/
Yadav, A., Gretter, S., Good, J., McLean, T. (2017). Computational thinking in teacher education. En P. Rich, C. Hodges (Eds.) Emerging research, practice, and policy on computational thinking (pp. 205-220). Springer. https://doi.org/10.1007/978-3-319-52691-1_13
Kong, S. C., Lai, M., Sun, D. (2020). Teacher development in computational thinking: Design and learning outcomes of programming concepts, practices and pedagogy. Computers & Education, 151. https://doi.org/10.1016/j.compedu.2020.103872
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