Ancient Chinese philosophical thinking, as an important part of Chinese civilization, has influenced thousands of years of Chinese history and also had a profound impact on the Ideological and Political Education in modern colleges and universities. Based on the philosophical nature of Ideological and Political Education, the article analyzes the learning styles of different categories and establishes a blended-tiered teaching model for Ideological and Political Education with the aid of digital technology. Based on students’ online Ideological and Political education learning behavior data, a Bayesian discriminant analysis algorithm is used to identify students’ learning styles. Then, the GRU neural network model is introduced to define the diagnosis of the knowledge level of Ideological and Political Education, and the Ideological and Political Knowledge Level Diagnosis Model is established. An example analysis was conducted to assess the learning style, cognitive level, and relevance of Ideological and Political Education. The study shows that when carrying out the identification of students’ learning styles, the Bayesian discrimination improves by 10.98% compared with the results of the style clustering algorithm, and the average absolute error of the diagnosis of students’ Civics knowledge level minimizes only 0.128. The scores for various learning styles are highly variable, and the extreme differences are all over 24 points. The standardized regression coefficients of learning interest in Ideological and Political courses and literacy learning styles are between 0.072 and 0.163, with a very significant correlation. Incorporating ancient Chinese philosophical ideas into ideological and political education is conducive to satisfying students’ multiple learning styles and also contributes to modernizing and preserving ancient philosophical ideas.
