This paper reforms the teaching of an existing computer operating system course based on the deep learning route DELC model and evaluates the teaching effect of the reform by means of empirical research. According to the loop framework of the DELC model, design innovative teaching objectives, teaching environments, and other aspects for the computer operating system course. We selected the control class and the experimental class in the School of Computer as research subjects for our teaching practice. The statistical analysis of the pre-test and post-test questionnaire data collected during the teaching practice was used to compare the questionnaire results of the control and experimental classes. Based on the test scores of the computer operating system course of the 10 classes of 2019–2023, cluster analysis and discriminative information were used to explore the teaching effect after the course reform in depth. The paper concludes that the average post-test scores of the experimental classes are significantly higher than those of the control classes, and they are 17.39% higher in the course recognition dimension compared to the control classes. Students of 2019-2022 are clustered into the “common” category, while students of 2023 who adopted the reform strategy in this paper are clustered into the “better” category. This fully demonstrates the feasibility and effectiveness of the proposed computer operating system course reform based on the DELC model.