Schools are the gathering centers of knowledge and information resources in the information society. In the new media environment, the traditional teaching method with paper textbooks as the main carrier cannot keep up with the pace of modern information technology (IT). The "Internet plus" smart campus model has become an inevitable trend of future university reform. This paper combined artificial intelligence (AI) with Big data (BD) and other advanced theories, used data mining to analyze students' learning, teachers' teaching behavior and the impact of related factors on education and teaching quality, and built a new generation of information platform. By utilizing various technological means to achieve resource sharing and interactive communication between teachers and students, as well as between different groups, a truly intelligent teaching service system was formed. School A, which deployed a smart campus information management system model based on BD and AI, was compared with School B, which used a traditional campus management platform. The experimental results showed that the average total score of students in Class A of School A was about 81.527 points, while the average total score of students in Class B of School B was about 77.979 points. Class A was about 3.548 points higher than Class B. This to some extent indicates that the application of AI and BD analysis technology can have a positive impact on education and teaching work, making teaching and management more refined. The introduction of BD and AI is driving the transformation of the entire society from an industrial economy to a knowledge-based economy. The personalized needs of students are gradually expanding and showing a diversified trend. Education concepts and teaching models have also undergone changes, bringing opportunities and challenges to schools.

Guangjian Ma. Intelligent Campus Informatization Management Model Based on BD and AI. The Frontiers of Society, Science and Technology (2023) Vol. 5, Issue 13: 71-77. https://doi.org/10.25236/FSST.2023.051312.

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