Sentiment Grading and Evaluation of Network Resources of Ideological and Political Education in Colleges and Universities: A Research Based on Artificial Intelligence.

Abstract

The current new round of scientific and technological revolution represented by artificial intelligence is rapidly driving a new wave of development of the times, and the rapid iterative update of science and technology is triggering new changes in educational concepts and educational thinking methods. Only by deeply understanding the reshaping of education concept, teaching concept, and learning concept by the new generation of scientific and technological revolution, as well as the major opportunities and challenges brought to education, can we understand the future direction of the development of ideological and political education for college students. This study takes the ideological and political education and teaching of college students as the research object. It begins by defining artificial intelligence and the ideological and political education of college students and analyzes the new concepts of precise individualization, intelligent teaching, and evaluation brought by artificial intelligence to the ideological and political education of college students. Then, it selects the students who have studied ideological and political education network resources as the empirical objects, designs a questionnaire based on the emotional characteristics of the resources, implements a questionnaire survey, uses the Stata software to conduct a correlation analysis on the acceptance of the students, and finally verifies the resources. Combined with empirical results, this article analyzes the influence of emotional characteristics of resources on students' acceptance, reveals the carrier role of ideological and political network resources in school emotional education and students through mirror theory and student response theory, respectively, and establishes the principle of graded reading guidance.