The increasing integration of Artificial Intelligence (AI), Internet of Things (IoT), and Machine Learning (ML) is creating new opportunities for intelligent and data-informed educational environments. However, applications of these technologies in physics education are often fragmented across instructional support, assessment, learning analytics, laboratory activities and institutional management, limiting their integration into a unified educational decision-support system. This study therefore designed an AI-IoT-ML framework for intelligent physics education and evidence-based educational administration in smart learning environments. The study adopted a Design Science Research (DSR) approach involving problem identification, objective definition, framework design and development, demonstration, conceptual evaluation, and communication. The proposed framework integrates a smart physics environment, IoT-based data acquisition, data processing and storage, ML analytics and prediction, AI decision support, and physics education and educational administration into a layered architecture with a continuous feedback mechanism. The framework provides potential applications in physics teaching and learning, student support, laboratory monitoring, equipment utilisation, resource management, scheduling, maintenance planning and evidence-based administrative decision-making. A key feature of the framework is its human-centred orientation, in which AI and ML provide analytical insights and recommendations while educators and administrators retain responsibility for professional judgement and final decisions. The study contributes a conceptual and architectural artefact that addresses the fragmentation between smart learning technologies, physics education and educational administration. The framework provides a foundation for subsequent prototype development, simulation and empirical evaluation of intelligent physics learning environments.

REFERENCES

[1]. Alfredo, R., Echeverria, V., Jin, Y., Yan, L., Swiecki, Z., Gašević, D., & Martinez-Maldonado, R. (2024).Human-centred learning analytics and AI in education: A systematic literature review. Computers and Education: Artificial Intelligence, 6, 100215. https://doi.org/10.1016/j.caeai.2024.100215

[2]. Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54, 977–997. https://doi.org/10.1007/s11165-024-10176-3

[3]. Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010

[4]. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

[5]. Ersozlu, Z., Taheri, S., & Koch, I. (2024). A review of machine learning methods used for educational data. Education and Information Technologies, 29, 22125–22145. https://doi.org/10.1007/s10639-024-12704-0

[6]. Ferreira, A., Oliveira, W., de Amorim Silva, R., Hamari, J., & Isotani, S. (2024). Internet of Things for smart education: A systematic literature review. In Z. Altinay, M. Chang, R. Kuo, & A. Tlili (Eds.), Proceedings of the 2024 IEEE International Conference on Advanced Learning Technologies (pp. 179–181). IEEE. https://doi.org/10.1109/ICALT61570.2024.00058

[7]. Hevner, A. R., & vom Brocke, J. (2023). A proficiency model for design science research education. Journal of Information Systems Education, 34(3), 264–278.

[8]. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105. https://doi.org/10.2307/25148625

[9]. Jacobsen, M., & McKenney, S. (2024). Educational design research: Grappling with methodological fit. Educational Technology Research and Development, 72, 2743–2762. https://doi.org/10.1007/s11423-023-10282-5

[10]. March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems, 15(4), 251–266. https://doi.org/10.1016/0167-9236(94)00041-2

[11]. Meylani, R. (2024). Transforming education with the Internet of Things: A journey into smarter learning environments. International Journal of Research in Education and Science, 10(1), 161–178.

[12]. Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO.

[13]. Palanci, A., Yılmaz, R. M., & Turan, Z. (2024). Learning analytics in distance education: A systematic review study. Education and Information Technologies, 29, 22629–22650. https://doi.org/10.1007/s10639-024-12737-5

[14]. Paulsen, L., & Lindsay, E. (2024). Learning analytics dashboards are increasingly becoming about learning and not just analytics: A systematic review. Education and Information Technologies, 29, 14279–14308. https://doi.org/10.1007/s10639 023-12401-4

[15]. Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77. https://doi.org/10.2753/MIS0742 1222240302

[16]. Roziqin, R., Samsudin, A., Saepuzaman, D., Sari, H. N., & Iryanti, M. (2026). Artificial intelligence inphysics education: A systematic review of content coverage, implementation models, learning impact, and pedagogical challenges. STEM Education, 6(4), 539–583. https://doi.org/10.3934/steme.2026023

[17]. Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252, 124167. https://doi.org/10.1016/j.eswa.2024.124167

[18]. Yeadon, W., & Hardy, T. (2024). The impact of AI in physics education: A comprehensive review from GCSE to university levels. Physics Education, 59(2), 025010. https://doi.org/10.1088/1361-6552/ad1fa2

[19]. 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, Article 39. https://doi.org/10.1186/s41239-019-0171-0

[20]. Azizi Kırıkkale, M. N., Faizi, A., & Sari, U. (2026). Artificial intelligence in physics education (2015– 2025): Systematic review of trends, applications, and challenges. Journal of Education in Science, Environment and Health. https://doi.org/10.55549/jeseh.905

[21]. Moundridou, M., Moutis, N., Charalampopoulos, K., & Matzakos, N. (2026). Generative AI in physics education: A PRISMA-guided systematic review of empirical studies. Artificial Intelligence and Applications. https://doi.org/10.47852/bonviewAIA62027183

[22]. Zhang, [details to be verified]. (2024). Methodological guidelines for design science research. Procedia Computer Science, 237, 195–203. https://doi.org/10.1016/j.procs.2024.05.096