Abstract How high school students understand chemical equilibrium is an important research issue that still has to be deeply explored. Latent variable modeling and data mining are beneficial for researchers to understand students' concept learning of chemical equilibrium from a new perspective. With the self-made chemical equilibrium proposition test, this study utilized the latent class analysis and Apriori algorithm to represent 722 grade eleventh students' mastery of the propositions regarding chemical equilibrium. The findings showed that students were appropriate to be divided into three groups, which groups were named high level of mastery group, intermediate level of mastery group, and low level of mastery group. Based on the conditions of parameters set in this study, no association rule was found in the responses of the high level of mastery group but a few association rules were found in those of the other two groups. Latent class analysis and Apriori algorithm can be utilized to study the learning of chemistry concepts and other issues.
MAI Yu-Hua, QIAN Yang-Yi, LAN Hai-Hang. Latent Class Analysis and Apriori Algorithm for Grade Eleventh Students' Mastery of Propositions Regarding Chemical Equilibrium[J]. Chinese Journal of Chemical Education, 2022, 43(17): 100-107.
