In today’s world, with the rapid development of information technology and scientific education, data technology has triggered important changes in ideological and political education in colleges and universities, effectively promoting the transformation of educational concepts, ways of thinking, educational methods, and practice modes. Based on the research background under big data, this study investigates the traditional knowledge-tracking model, introduces the attention mechanism and the characteristics of ideological and political learners on the basis of the traditional model, and proposes an improved knowledge-tracking model. At the same time, a mobile teaching platform was constructed, then the improved knowledge tracking model was tested, and the effect of the knowledge platform application on the relevant dataset was explored. The results show that using the optimized knowledge state tracking model, the teacher’s teaching time can be adjusted according to the students’ state, and there is a good effect on the prediction of students’ grades, and the average grade of the students is only 2-6 points of error from the predicted grades. In terms of model application accuracy, the average value of low accuracy is 6.92%, the average value of medium accuracy is 12.9%, and the average value of high accuracy is 79.79%, so the model assesses students’ knowledge status with high accuracy. Finally, the optimized model was used to analyze the learning effect of the students and to conduct a survey on the effect of using satisfaction, and the survey concluded that the students were more satisfied with the model.