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Practitioners and researchers interested in understanding student achievement, its predictors, and how it relates to other student outcomes are likely unaware of how the source information about achievement may offer subtly different pictures. This study applies multitrait–multimethod (MTMM) confirmatory factor analysis (CFA) within a structural equation modeling (SEM) framework to student achievement data to demonstrate empirically how commonly used measures of student achievement may reflect different information about student performance. Using student population-level data from a single state, this study presents a robust demonstration of the similarities and differences among three commonly used achievement measures—American College Testing (ACT) scores, state test scores, and grade point average (GPA). Results show that state assessment scores and ACT scores measured a similar achievement construct, whereas student grades reflected less of the achievement construct and a higher level of method effects. Possible sources of the similarities and differences among different achievement measures are discussed, along with implications for measurement among gifted students.

This brief examined the patterns of reading achievement using statewide data from all students (Grades 3–10) in multiple years to examine gaps based on student, school, and district characteristics. Results indicate reading achievement varied most between students within schools and that students’ prior achievement was the strongest predictor of current achievement. Achievement gaps were identified for males, Black students, students receiving meal subsidies, and schools with higher proportions of students receiving meal subsidies. A “clientele effect” was also found. Policy implications are discussed.