Volume 10,Issue 8
Data-Driven Decision-Making and Transformation of School Management: A Qualitative Case Study on the Integration of Educational Artificial Intelligence
In the contemporary landscape of global educational reform, the integration of educational data mining, smart campus infrastructures, and artificial intelligence into institutional governance represents a fundamental paradigm shift. Set against the strategic backdrop of China’s push toward digital educational transformation and the modernization of its educational governance capabilities, this research investigates the systemic transition from traditional heuristic administration to evidence-based, data-driven decision-making. As the vanguard institution of the R Primary School Education Group, T Primary School has navigated the complex intersection of advanced data analytics and its deeply humanistic “Renhe” (people-oriented harmony) cultural philosophy. Through an in-depth thematic analysis of institutional practices, leadership directives, and localized pedagogical frictions, this study elucidates how data-driven frameworks are operationalized in curriculum development, continuous formative evaluation, and cognitive-behavioral tracking. The findings reveal that while quantitative data systems significantly optimize resource allocation and enable personalized learning pathways, they are inherently insufficient without qualitative human contextualization. The study highlights profound epistemological and organizational challenges, including stakeholder resistance, the limitations of purely quantitative metrics in capturing student motivation, and the ethical imperatives of privacy within distributed collective decision-making models. Ultimately, this report proposes a transition from rigid “data-driven” mandates to nuanced “data-informed” leadership ecosystems, offering critical theoretical and practical implications for the deployment of trustworthy AI and educational large models in modern school governance.
[1] M. Jing, Z. Guo, X. Wu, Z. Yang, and X. Wang. 2025. Higher education digital academic leadership: perceptions and practices from Chinese university leaders. Education Sciences 15, 5, 606. https://doi.org/10.3390/educsci15050606
[2] A. Bettahi, F. Z. Beloudha, and H. Harroud. 2025. Continuous-time modeling in educational data mining and learning analytics: a literature review on methods, ethics, and emerging AI trends. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3622103
[3] C. Lee, E. M. Camburn, and J. Sebastian. 2025. School context, school leaders’ data-informed decision making, and student achievement: evidence from Florida. School Effectiveness and School Improvement 36, 1, 45–70. https://doi.org/10.1080/09243453.2024.2436889
[4] E. Brazauskienė. 2025. Educational decision-making in digital education: a conceptual review of data-driven, data-based, and data-informed approaches. Institutul pentru Educatie 4, 1, 63–72. https://doi.org/10.61071/RPD.2562
[5] L. R. López-Morocho, V. März, S. Biémar, C. Jaramillo-Baquerizo, M. H. Pavo, and M. Frenay. 2025. Beyond numbers: practices, perceptions and challenges of data-informed decision-making in Ecuadorian schools. In Proceedings of ICERI2025, 4995–5002. IATED. https://doi.org/10.21125/iceri.2025.1411
[6] H. Azizi, M. S. Amini, S. Sulaimany, and A. Mafakheri. 2025. Visibility graph analysis for educational data: potentials and a case study of predicting at-risk online students. Scientific Reports 15, 1, 32036. https://doi.org/10.1038/s41598-025-17760-1
[7] M. M. Rust and B. A. Motz. 2025. Incorporating an LMS learning analytic into proactive advising: validity and use in a randomized experiment. The Internet and Higher Education 101057. https://doi.org/10.1016/j.iheduc.2025.101057
[8] F. Marques, A. Ortiz-Beltrán, D. Hernández-Leo, and C. Castillo. 2025. Institutional, academic, and learning analytics: a bibliometric study. In Proceedings of the 2025 IEEE International Conference on Advanced Learning Technologies (ICALT), 131–133. IEEE. https://doi.org/10.1109/ICALT64023.2025.00043
[9] S. Palarimath, B. Dhanasekaran, S. Kumar, and A. Dubey. 2025. Smart campus, smarter students: enhancing learning outcomes through AI‑IoT‑enabled sustainable spaces. In Proceedings of the 2025 10th International STEM Education Conference (iSTEM-Ed), 1–6. IEEE. https://doi.org/10.1109/iSTEM-Ed65612.2025.11129276
[10] L. Wei, Y. Yu, Y. Qin, and S. Zhang. 2025. Design of an Internet of Things data collection and computing-based decision support framework for educational management for smart campus. J. COMBIN. MATH. COMBIN. COMPUT 127, 6965–6980. https://doi.org/10.61091/jcmcc127b-380
