Analysis the Innovation Path on Psychological Ideological with Political Teaching in Universities by Big Data in New Era

Abstract

The increasing pressure of life and the rapid development of the economy have caused huge mental health situation problems for people. Mental health situation has an important relationship with one’s own life values. The cognition Ideological with political is to improve people’s optimistic attitude and values. The students of college will face enormous pressure from their studies, which can easily causes the mental health situation problems. However, the psychological and ideological education in universities still adopts the traditional teaching method, which reduces students’ learning hobbies and learning efficiency. This also reduces students’ understanding of the content of psychological ideological with political teaching. Big data theory can process complex research object data and relationships. It can help researchers discover characteristic factors related to psychological ideological with political teaching. This study uses the hole convolution in big data theory and GRU technology to analyze the three factors of student behavior characteristics, mental health situation content characteristics, and the cognition Ideological with political content characteristics in college psychological the cognition Ideological with political. The research results show that the atrous convolution and GRU methods can more accurately predict the three characteristics of psychological ideological with political teaching in universities. This is helpful for educators to discover more appropriate psychological and ideological with political teaching methods.