Students’ success in introductory college-level chemistry courses is important for them to continue to more advanced science courses and to progress toward science-related careers. Previous studies indicate that both cognitive and non-cognitive variables are relevant for student success. In this study, Structural Equation Modeling (SEM) was used to predict students’ achievement in chemistry from both cognitive (math ability, prior conceptual knowledge in chemistry) and non-cognitive (attitude toward chemistry) measures. The purpose of this study is to investigate which of three alternative SEM models best represents the relationships among these variables and achievement in chemistry, and what proportion of variance in chemistry achievement can be explained. Results provide support for using a SEM model with all three predictors, with 69% of the variance in chemistry achievement explained. Both prior conceptual knowledge and attitude toward chemistry contribute a significant unique portion to the prediction of chemistry achievement when controlling for math ability. The results suggest that instructors can improve students’ achievement in chemistry not only by focusing on helping them to build conceptual knowledge, but also by fostering their positive attitude toward chemistry. This study also has implications for SEM researchers, both to further replicate the study in other contexts, and to add other potentially relevant predictors. Instrument developers may also use the modeling strategy as a springboard for optimizing assessment tools.
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