With the development of information technology and the advancement of education informatization, the use of mathematical modeling and extensive data analysis technology makes the realization of precision education possible. In this paper, we study the problem of precise teaching intervention from the perspective of multi-stage decision-making, introduce a reinforcement learning algorithm, portray the process attributes and temporal characteristics of teaching, use a Q-learning algorithm to construct a general framework for precise teaching intervention, and through the empirical study of Ideologicalcs teaching in colleges and universities, we show the specific application of this framework in teaching practice and analyze the digital transformation path of the Ideologicalcs education in colleges and universities. The results show that under precise teaching intervention, the students’ pre-post test scores of each Ideologicalcs behavioral characteristic index are significantly different at the 0.05 level. This study helps improve students’ learning effectiveness and provides support for teachers to conduct precise ideological teaching.