In the era of digital intelligence technology, ideological and political education is undergoing paradigm shift through the construction of cognitive maps, reconstruction of immersive scenarios, reshaping of subject relationships, and innovative dynamic evaluation. Based on multi-source data fusion and reinforcement learning algorithms, a precise adaptation system of “data collection—cognitive modeling—dynamic intervention” is constructed; Using virtual reality, emotional computing and other technologies to create embodied educational scenes that promote the coexistence of reality and virtuality, and promote the internalization of values and emotional resonance; Building a data ethics barrier based on technologies such as federated learning and blockchain, promoting the evolution of educational subjects and objects towards a human-machine collaborative ecosystem; Innovative LSTM(Long Short-Term Memory)time series model and DBN(Dynamic Bayesian Network)are used to construct a full cycle evaluation system, achieving three-dimensional dynamic diagnosis of “cognition—emotion—behavior”. Research aims to break through the limitations of traditional education in terms of time and space through technological empowerment. It not only enhances the scientific nature of education through dynamic modeling and algorithm optimization, but also safeguards the essence of education through the integration of values embedding and Marxist methodology, providing innovative solutions for the modernization of ideological and political education in the New Era.