| Despite high-stakes applications of assessment findings, assessment data are frequently collected in situations that are of low-stakes to examinees. Because low-stakes tests are of little consequence to the examinees, test-taking motivation and thus the validity of inferences drawn from unmotivated examinees' scores are of concern. The current study explored examinee self-reported effort in a several-hours long low-stakes testing context via both structural equation mixture modeling and latent growth modeling approaches. Structural equation mixture models of varying complexity and parameterization were estimated and external criteria validity evidence for two- and three-class solutions were considered. Prior to interpreting the structural equation mixture modeling findings, aggregate trajectories of growth were explored via latent growth modeling. However, with the exception of a linear model of effort for the three cognitive tests, which suggested slight decline in aggregate effort across the three cognitive tests, none of the models exhibited adequate model-data fit. Consequently, an indirect approach to interpreting the three-class solution of the structural equation mixture modeling results provided a heuristic for understanding examinee motivation in the low-stakes context. External criteria related to effort, such as goal orientations, self-efficacy for mathematics, and personality variables contributed to explanations for three classes of examinees: higher-effort, mid-effort, and lower-effort. Expectancy-value theory, personality traits, and fatigue explanations of examinee motivation in a low-stakes context are considered. |
