Achieving Equity for Latino Students
This book provides a critical discussion of the role that select K–12 educational policies have and continue to play in failing Latino students.
Contemporary Educational Psychology / May 2020
Expectancy-value researchers have described the components of subjective task value in multiple ways, leading to multiple competing structural representations of subjective task value data. The purpose of this study was to examine these competing multidimensional factor structures by comparing correlated factor, hierarchical, and bifactor representations of both confirmatory factor analysis and exploratory structural equation modeling (ESEM) models across three theoretical conceptualizations of subjective task value. Results indicate that, in an undergraduate life science learning context (n = 334), the best representation for subjective task value data was a bifactor ESEM model that allowed for the disentangling of general and specific variance of general subjective task value, specific value beliefs, and specific costs. This measurement and modeling approach achieved full measurement invariance of the retained structure across continuing generation and first-generation students, and no differential item functioning was found across gender. General subjective task value, specific value beliefs, and specific cost factors estimated in this model predicted achievement, confirming the criterion-related validity of general and specific factors for predicting achievement outcomes.