The Utilisation of Artificial Intelligence Applications as a Catalyst for the Transition towards Student-Centred Pedagogical Practices: The Following Essay Presents a Qualitative Analysis of Implemented Educational Scenarios in Primary Education
DOI:
https://doi.org/10.5281/zenodo.18932662Abstract
This study investigates the extent to which the use of Artificial Intelligence (AI) applications in primary education teaching scenarios contributes to the transformation of teaching towards student-centred practices. The research was conducted as part of a distance learning programme on Human-Centred AI, in which 164 teachers designed and implemented scenarios in authentic school environments. A qualitative approach was adopted, with a descriptive case study and systematic content analysis using a specially designed tool to record student-centred teaching axes. The findings indicated an overall high level of student-centred integration of TN (mean 4.10/5), with notably high performance in active and exploratory learning, creativity, and critical thinking. In contrast, differentiated teaching exhibited a comparatively lower value. In conclusion, the pedagogically documented use of TN has the potential to catalyse the transition to truly student-centred learning environments, provided that there is systematic training and targeted pedagogical planning.
References
Anastasiades, P., Kotsidis, K., Stratikopoulos, K. & Pananakakis, N. (2024). Human– Centered Artificial Intelligence in Education. The critical role of the educational community and the necessity of building a holistic pedagogical framework for the use of HCAI in the education sector. Open Education – The Journal for Open and Distance Education and Educational Technology, 20(1), 29–51. https://doi.org/10.12681/jode.36612
Aravantinos, S., Lavidas, K., Voulgari, I., Papadakis, S., Karalis, T., & Komis, V. (2024). Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus. Education Sciences, 14(7), 744. https://doi.org/10.3390/educsci14070744
Bremner, N. (2021). The multiple meanings of ‘student-centred’ or ‘learner-centred’ education, and the case for a more flexible approach to defining it. Comparative Education, 57(2), 159–186. https://doi.org/10.1080/03050068.2020.1805863
Bryman, Α. (2016). Social Research Methods (5th ed.). Oxford University Press.
Hwang, G.-J., & Chen, N.-S. (2023). Editorial Position Paper: Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions. Educational Technology & Society, 26(2). https://www.jstor.org/stable/48720991
Holmes, W., Iniesto, F., Anastopoulou, S., & Boticario, J. G. (2023). Stakeholder perspectives on the ethics of AI in distance-based higher education. International Review of Research in Open and Distance Learning, 24(2), 96–117. https://doi.org/10.19173/irrodl.v24i2.6089
Hwang, G.-J., Xie, H., Wah, B. & Gašević, D. (2020).Vision, challenges, roles and research issues of Artificial Intelligence in Education, Computers and Education: Artificial Intelligence, 1. https://doi.org/10.1016/j.caeai.2020.100001
Kotsidis, K. & Anastasiades, P. (2025). Empowering Teachers through Human-Centred Artificial Intelligence: Evaluating a Distance Training Program in Education. AI Enhanced Learning, 1(2), 327–343. https://doi.org/10.70725/976906blfywu
Mills, E.G., Gay, L.R., & Airasian, P. (2019). Educational Research: Competencies for Analysis and Applications (12th ed.). Pearson.
Van Geel, M., Keuning, T., Frèrejean, J. , Dolmans, D., van Merriënboer, J., & Visscher, A. J. (2019). Capturing the complexity of differentiated instruction. School Effectiveness and School Improvement, 30(1), 51–67. https://doi.org/10.1080/09243453.2018.1539013
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Konstantinos Kotsidis

This work is licensed under a Creative Commons Attribution 4.0 International License.