Using factor mixture modeling to identify dimensions of cognitive test anxiety

Abstract

The research on test anxiety has repeatedly attempted to provide a more refined measurement of multiple dimensions of the construct. Divergence in the field has repeatedly arisen in the specific dimensions, but there is a broad acceptance that there are various manifestations of test anxiety. The current study attempts to specifically explore the potential for identifying subcomponents of the construct referred to as cognitive test anxiety. The analyses did not support the initial prediction that a temporal determination of factors (i.e., related to the Learning-Testing Cycle) would arise. Alternatively, exploratory factor mixture modeling (EFMM) demonstrated that there were two latent classes of students (based on levels of reported test anxiety). Furthermore, the EFMM demonstrated that the factorial structure of cognitive test anxiety differed between these two latent classes. Specifically, undergraduate students with low levels of cognitive test anxiety represented cognitive test anxiety as a unidimensional construct. However, for those students with high levels of test anxiety, there were two distinct factors. The results suggest that those learners with high-test anxiety are able to differentiate among more different “types” of test anxiety as compared to their non-anxious peers.