Abstract
Achievement motivation scores on the domain-specific level are better predictors of domain-matching scholastic performance than scores of general achievement motivation measures. Although there is research on domain-specific motivational measures, it is still unknown where this higher predictive power originates from. To address this, 715 students in secondary school answered questionnaires on general and domain-specific achievement motivation, domain-specific self-concept, and domain-specific self-esteem in two different studies. The first study was designed to disentangle the variance components in general and domain-specific achievement motivation in order to delineate hypotheses regarding potential drivers for the predictive power of domain-specific achievement motivation. The findings implied a strong role for a shared method factor. To explore the nature of this method factor, domain-specific self-concept/-esteem were focussed to establish discriminant validity evidence in a second study. The results indicate that the additional domain-specific variance can, in large parts, be explained by self-concept and self-esteem on domain-specific level.
Highlights
The current results show that the role of each domain-specific method factor for the test-criterion correlation strongly deteriorates when controlling for domain-specific self-concept and self-esteem
Prior research showed that domain- phrased achievement motive scale scores yield better test-criterion correlations when predicting scholastic performance
Our studies built on this research and aimed to contribute towards a clearer picture of the specific contributions to test-criterion correlations different variance components in those test scores might have
Summary
In a second analytical step, different school grades (math, physics, German) were integrated into the preferred model (Models 2a–c) and regressed on the latent trait and method factor(s). This model informs us about the specific role each variance source has for the test-criterion correlation. The sample consisted of 390 students attending a German secondary school type that prepares for university (Gymnasium) (231 girls, average age 17 years [SD 1⁄4 1.06]). For the CTC(M-1) model a sample size of N 1⁄4 402 was estimated to have sufficient power for a model with 5 degrees of freedom. There were substantial loadings from the latent method factor for each domain. The amount of explained variance for math grades was larger, mainly due to the regression weight of the method factor
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