Research on the Optimization Path of Student Management Strategies Driven by Artificial Intelligence on the Cultivation of Innovative Ability of Students in Colleges and Universities

Abstract

Based on artificial intelligence management, this paper takes students’ innovation ability as the research object and adopts the improved Apriori algorithm for mining, feature selection and data correlation of the survey data through the questionnaire survey method. With the purpose of improving students’ innovation ability, we summarize the factors affecting the cultivation of students’ innovation ability in colleges and universities and provide new ideas for the optimization of management for the improvement of students’ innovation ability driven by artificial intelligence. The experimental results found that there is no significant difference in the scientific research and innovation ability of master’s students in different grades, while the F-value of the type of undergraduate institution and the type of master’s institution on the scientific research and innovation ability of master’s students (21.121, 45.609) reaches a significant level (P < 0.01). The level of research and innovation ability of master’s students showed a high correlation with the P-value of all 4 factors of students under AI-assisted management < 0.01. The empirical analysis verified that all the variables related to university student management strategies have a significant effect on students’ innovation management ability. Obviously, artificial intelligence provides a new program for cultivating students’ innovative abilities.