It is against this background of the transformation of the system of higher education governance and the reinforcement of the value guidance in the new era that the mechanism of college students becoming integrity cognition have the features of multidimensional coupling and dynamic evolution. With the overarching aim of moral education and talent development, this paper combines insights based on pedagogy, cognitive science and data mining technology to conduct a review and critically examine the development trajectory of integrity cognition among college students. Through the introduction of techniques of multi-source data fusion, text mining, clustering analysis, and path modeling, an analytical paradigm of value input-cognitive processing-behavioral transformation is built, and the dynamics of change of the integrity cognition structure under various educational intervention models is outlined. The study concludes that integrity cognition does not lie in the accumulation of knowledge as a single entity and that it is a complex system that is collectively influenced by value internalization, situational experience and behavioral feedback. Data mining technology proves to be of great benefit in detecting differences in cognitions, forecasting development patterns, and streamlining learning paths. Moreover, this article presents a specific intervention model of integrity education based on the data, which should be a precise model, with theoretical justifications and practical examples to support ideological and political education in universities.