Construction and Analysis of College Students’ Ideological Education System Based on Artificial Intelligence Technology

The combination of intelligent algorithms and the education system of colleges and universities is an inevitable trend for the high-quality development of college teaching in the era of big data. In this paper, for the problem of cumbersome and time-consuming resource search on educational resource websites, it is proposed to utilize the LSTM algorithm, add the combination of input features based on the attention mechanism, and design and form a new intelligent search algorithm based on semantic analysis. Combined with the intelligent search steps of ideological and political education resources, the search results of ideological and political education resources are optimized. Carry out text and image search tasks in the ideological education field dataset, and evaluate the search performance of this paper’s algorithm and other algorithms using MAP and top-k Precision evaluation indexes. Combined with teaching applications, analyze the teaching impact of ideological education resources in colleges and universities based on intelligent search algorithms. Based on the ideological education domain dataset, the algorithm model of this paper can improve the MAP performance on different search tasks, and as the value of K increases, the Precision values of this paper’s algorithm are 0.431 and 0.411, which are obviously better than the RNN algorithm. Comparing the students’ three teaching performance, the education system constructed in this paper can help to improve the students’ ideological education performance.