The current study explored the associations between non–cognitive science-related variables, i.e., science interest, utility, self-efficacy, science identity, and science achievement in a serial mediation model. The study also further explored the potential heterogeneity in the model parameters using one of the data-mining techniques, which is the structural equation model (SEM) Tree. Data on 14,815 high school students were obtained from a large-scale database High School Longitudinal Study of 2009 (HSLS:09). The results highlighted science interest and science utility positively influencing science achievement through a sequential pathway of mediators, including science self-efficacy and science identity. The strength of direct effects considerably varied across students, resulting in classifying them into four subgroups. For instance, among females with a low SES subgroup, developing substantial science interest would result in better science self-efficacy and science identity that flourish science achievement. These valuable findings provide fruitful tailored recommendations, elevating the science achievement in the subgroups (146 words).
The Influence Of Enrollment In Agriscience Courses On The Science Achievement Of High School Students
