Using social network analysis method to explore the cognitive knowledge structures of different high school student groups on the topic of "ethanol"

Abstract

This study used a graph theory-based social network analysis method to explore the cognitive knowledge structures of groups of high school students with different achievement levels on the topic of ethanol. Its aim was to provide practical suggestions for the classroom-based teaching of different student groups. Semi-structured interviews were used to collect data on the ethanol knowledge of students at three different achievement levels from a high school in Shenzhen, China. Each of these three levels consisted of 23 students, for a total of 69 students. Interviews were conducted with the students one week after they had received ethanol instruction. Subsequently, interview records for each student were transformed into an individual-student co-occurring phrases matrix. The co-occurring phrases matrices of the 23 students in each group were ultimately combined into a larger group co-occurring phrases matrix for evaluation using social network analysis. Data on cognitive knowledge structures were analyzed along three dimensions: structural features, content based on organizational features, and learning difficulties. The results revealed that, on the topic of ethanol, 1) the students with the highest academic achievement constructed a cognitive knowledge structure with more nodes, connections, and greater integration compared to the group with the lowest academic achievement; 2) the organization and content of the cognitive knowledge structures on ethanol differed among different student achievement levels; e.g., the nodes categories with the ability to control the exchange of information were more diversified in the high-achieving student group, while those of the low-achieving group were more homogeneous, and the organization of the former’s cognitive knowledge structure was clearer than that of the latter; and 3) all student groups experienced learning difficulties with certain ethanol contents, including odor, symbolic representation, oxidation by strong oxidants, and structure–property linkages.