Abstract: A new cognitive diagnostic framework was proposed to evaluate students' theoretical and practical abilities in computer science education. Based on the probability graph model, students' coding ability was introduced, then the students' theoretical and practical abilities was modeled. And a parallel optimization algorithm was proposed to train the model efficiently. Experimental results on multiple data sets show that the proposed model has a significant improvement in MAE and RMSE compared with the competing methods. The proposed model provides more accurate and comprehensive analysis results for computer science education.