This study is a research-based analysis of how China integrated big data technology into education along with the major challenges involved, machine learning algorithm usage, and training I.T. management frameworks. It was determined that the main obstacles to Big Data implementation were the reliability of information, privacy issues, and institutional infrastructure. These challenges were addressed by implementing machine learning algorithms such as the LightGBM, XGBoost, SVM, and RF to develop a universal IT management framework. Through this approach, teachers attempted to determine teaching strategies based on the analyzed educational data patterns and future adherence and effectiveness of students to school education. Using usability analyses the platform was performing effectively and easy for educators as well as students to apply in their practice. The research results showed that these strategies provided a change to an approach not only to the methods of teaching but also to improve the quality of educational outcomes and the development of a modern system of education. The solutions proposed include promoting communication and collaboration between the IT leaders, instructors, and scientists by ensuring that they work together to overcome the challenges, taking also longitudinal studies to measure the long-term achievements and impact of the IT management design on teaching and student accomplishment. To this end, research works on this topic will aid the development of educational practices by using big data technology and machine learning algorithms to develop strategies for the betterment of educational outcomes in China.
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