New Perspectives in Science Education

The development of Computational Thinking (CT) offers a powerful approach to enhancing science teaching in preschool and primary education [1]. However, this requires well-trained teachers capable of navigating complex technological environments [2]. This study describes the methodology and design of an adaptive gamification environment designed to equip pre-service teachers with essential CT competencies. Integrated into a professional development program grounded in the Technological Pedagogical and Content Knowledge (TPACK) framework [3, 4] the environment utilizes a custom application that adapts game mechanics and content to users based on the Hexad player model [5]. The methodology unfolds in two distinct stages. Firstly, participants engage with the four CT concepts through problem-based gamified activities unrelated to programming [6, 7], employing AI-driven Intelligent NPCs [8] to personalize the learning experience and link these concepts to science education. The second stage utilizes a "play-modify-create" approach within a block-based programming environment [3]. Teachers apply the "to play, to think, to code" pedagogy by analysing finished programs, decomposing logic, and transforming plans into code through testing. Crucially, the system provides real-time learning analytics to the teacher educator throughout both stages. This data equips the educator to monitor progress and assist them with greater precision, effectively utilizing educational data in technology-rich settings.

[1] Ogegbo, A. A., & Ramnarain, U. (2022). A systematic review of computational thinking in science classrooms. Studies in Science Education, 58(2), 203-230. https://doi.org/10.1080/03057267.2021.1963580

[2] Papadakis, St., Zourmpakis, A., Kasotaki, S., & Kalogiannakis, M. (2024). Teachers’ Perspectives on Integrating Adaptive Gamification Applications into Science Teaching, Journal of Electrical Systems, 20(11s), 2024, 2593-2600, https://doi.org/10.52783/jes.7917

[3] Kong, S. C., & Lai, M. (2022). A proposed computational thinking teacher development framework for K-12 guided by the TPACK model. Journal of Computers in Education, 9(3), 379-402. https://doi.org/10.1016/j.compedu.2022.104562

[4] Zourmpakis, A.-I., Papadakis, St., & Kalogiannakis, M. (2022). Education of Preschool and Elementary Teachers on the Use of Adaptive Gamification in Science Education, International Journal of Technology Enhanced Learning (IJTEL), 14(1), 1-16, https://doi.org/10.1504/IJTEL.2022.120556

[5] Zourmpakis, I.-A., Kalogiannakis, M., & Papadakis, St. (2023). A Review of the Literature for Designing and Developing a Framework for Adaptive Gamification in Physics Education. In M.-F. Taşar and P.-R.-L. Heron (Eds), The International Handbook of Physics Education Research: Teaching Physics, 5.1-5.26, Melville, New York: AIP Publishing, https://doi.org/10.1063/9780735425712_005

[6] Ng, A. K., Atmosukarto, I., Cheow, W. S., Avnit, K., & Yong, M. H. (2021). Development and implementation of an online adaptive gamification platform for learning computational thinking. In 2021 IEEE Frontiers in Education Conference (FIE) (pp. 1-6). IEEE. https://doi.org/10.1109/fie49875.2021.9637467

[7] Zourmpakis, A. I. (2025). Developing Computational Thinking in Early Childhood Education: Long-Term Impacts on CT Skills and Motivation Using the CAL Approach, ScratchJr, and Gamification. Advances in Mobile Learning Educational Research, 5(2), 1536-1547. https://doi.org/10.25082/AMLER.2025.02.009

[8] Campitiello, L., Beatini, V., & Di Tore, S. (2024). Non-player character smart in virtual learning environment: Empowering education through artificial intelligence. In Workshop on Artificial Intelligence with and for Learning Sciences: Past, Present, and Future Horizons (pp. 131-137). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-57402-3_14