Innovative Analysis of Student Management Path Based on Artificial Intelligence and Big Data Integration

Abstract

This paper discusses the application path and effect evaluation method of big data and artificial intelligence in college student management, aiming at promoting the intelligent and humanized development of management through technological innovation. A BP neural network model (IFOA-IAGA-BP) based on the combination of improved firefly optimization algorithm (IFOA) and improved artificial pigeon colony algorithm (IAGA) is studied and constructed, aiming at improving the accuracy and efficiency of management quality evaluation. This model can identify students' individual needs more accurately, optimize the allocation of teaching resources, improve teaching quality, predict students' learning risks through intelligent algorithms, intervene in time, and provide all-weather learning consultation services, so as to enhance the immediacy and effectiveness of student support services.