A Framework for Constructing Cognitive Diagnostic Reports on English Reading for Chinese University Students

In the context of higher education in China, improving students’ English language proficiency has become a critical task, as English plays an increasingly important role in academic development and career success. However, traditional summative assessment methods, such as the College English Test Band 4 and Band 6 (CET-4 and CET-6), mainly provide scores or rankings. These abstract results fail to offer detailed insights into students’ strengths and weaknesses in reading comprehension. As a result, they do not fully serve the purpose of assessment or meet students’ practical needs. With the advancement of information technology, the application of computer-based approaches in education has gained growing attention. Cognitive diagnostic models, which provide detailed and fine-grained analysis, align well with Chinese students’ needs for personalized feedback. This study adopts the Generalized DINA (G-DINA) model to analyze students’ English reading performance and generate personalized diagnostic feedback reports. The results show that the G-DINA model fits the college English reading test data effectively and yields meaningful diagnostic information. A survey of students’ feedback and suggestions reveals that most students responded positively to the content and design of the feedback reports. They believed that personalized feedback enhanced their learning experience and contributed to instructional improvement. By incorporating cognitive diagnostic assessment into English reading instruction, this study proposes a more accurate, data-driven feedback approach. It addresses the limitations of traditional assessments and supports more targeted teaching improvements in English education at Chinese universities.