ABSTRACT
Finally, between groups (where coefficients are unstandardized betas), we can see that low student SES composition positively predicts membership in C#1 versus the reference class (0.229, p < 0.06), negatively predicts membership in C#2 (–0.860, p < 0.05), and positively predicts membership in C#3 (0.456, p < 0.05). The results are therefore consistent with the theoretical propositions that student achievement background (GPA) and SES are related to different latent classes of science growth within schools and that student composition is associated with different latent classes of school science growth between schools.
