Design of big data analysis and intelligent decision support system in student work management

With the growth of artificial intelligence (AI) and big data technology, digital campus construction has been widely applied. However, the continuous expansion of the scale of college students and the increasing complexity of student affairs have made the traditional student work management model inefficient. In this context, big data analysis and machine learning (ML) algorithms have shown broad application prospects in campus management decision-making, teaching quality improvement, and student service optimization. Through big data analysis technology, valuable information for education managers and learners can be extracted from massive amounts of data, thereby discovering and solving various problems in educational research and practice. Based on this, this article proposes an intelligent decision support system based on big data analysis and AI technology. This system integrates multi-source heterogeneous data of students on campus, deeply explores students' behavior patterns and demand patterns, and predicts students' academic risks, providing accurate and scientific decision-making basis for educational managers. The results indicate that the system can efficiently implement student academic warning and help schools take timely intervention measures.