<p>In order to enhance the country’s innovation capacity and build a highly-skilled national talent pool, China aims to build a modern education system by 2035. However, current methods for evaluating and improving the curriculum system are often subjective, do not pay sufficient attention to student learning outcomes, and are not based on scientifically valid models. To address this issue, we propose a factor analysis-based method for evaluation and improvement of the curriculum system. First, we applied a confirmatory factor analysis model to assess the current ‘courses – graduate attributes’ support matrix. Next, we performed exploratory factor analysis to provide insights into potential conflicts between the factor loading-based matrix and the original support matrix. Finally, we convened a teaching steering committee meeting that resulted in an improved support matrix that offers more objective, data-driven guidance through human–machine collaboration. A case study of a <i>Digital Electronic Technology</i> course demonstrates the refined matrix’s application in designing course objectives and assessments. By using factor analysis to provide a scientific basis for evaluating and improving the curriculum system, this study assists educators in preparing higher quality self-evaluation reports for engineering education accreditation. While this study focuses on engineering education, the methodology is equally applicable to political science, where it can help identify relationships between curricula and the development of essential skills. This approach not only aligns with national educational goals but also strengthens the overall curriculum system.</p>