USING BAYESIAN NETWORKS FOR COGNITIVE DIAGNOSIS ASSESSMENT OF UPPER-SECONDARY SCHOOL STUDENTS UNDERSTANDING IN REDOX REACTION

The redox reaction is a core concept of upper-secondary school chemistry curriculum. Accurate diagnosis of students’ conceptual understanding of the redox reaction from a cognitive structure perspective is critical for enhancing their understanding of chemical concepts. This study utilized Bayesian networks to investigate the cognitive structures of Chinese students regarding the redox reaction. A total of 409 upper-secondary school students participated, with 227 in 11th grade and 182 in 12th grade. Seven cognitive attributes related to the redox reaction were identified, and their hierarchical relationships were mapped. The research process of cognitive diagnosis assessment of redox reaction based on Bayesian network was developed. The results indicated that Bayesian networks can effectively assess students’ cognitive structures of the redox reaction. Key attributes identified in students’ cognitive structures were "electron transfer", "oxidation reaction / reduction reaction" and "oxidability / reducibility". Furthermore, a comparison of the cognitive structures between 11th and 12th graders showed that 12th graders had a more advanced understanding with fewer conceptual gaps, while 11th graders demonstrated less developed cognitive pathways, which may be attributed to a lack of deep conceptual understanding. Keywords: Bayesian network, cognitive diagnostic assessment, redox reaction, cognitive structure