Science achievement within the United States: a view through affective and demographic lenses

ABSTRACT

This study investigated the predictive effects of science self-efficacy, value in learning science, science attitudes, gender, and race on science achievement, among United States middle school students utilising Trends in International Math and Science Study 2011 data. A series of preliminary analyses using several descriptive statistics, Cronbach alpha, and exploratory factor analysis, were conducted. The main analysis of the study was Structural Equation Modelling (SEM), utilising both measurement models and structural models. Findings indicated that science self-efficacy, value in learning science, gender and race were significant positive predictors of science achievement, while attitude was not a predictor. Male students showed higher science achievement, science self-efficacy and science attitude than females. White and Asian students showed significantly higher science achievement, science self-efficacy, value in science learning, and science attitudes than Black and Hispanic students. These findings may be utilised to implement new science programs and encourage and train educators.

KEYWORDS:

• Science achievement
• self-efficacy
• value in learning science
• student attitude
• racial differences
• gender differences

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Susie M. Cohen

Susie M. Cohen is a PhD Candidate at Florida International University in the Teaching and Learning department. She is currently a research assistant at the STEM Transformation Institute. Prior to attending FIU, she was an elementary/middle school science teacher and served as an adjunct professor at two universities. Her dissertation interests include early STEM experiences and the relationship to STEM identity and career choice.

Mido Chang

Mido Chang is a Professor of Educational Research Methodology in the College of Arts, Sciences and Education at Florida International University. Dr. Chang teaches research method courses including structural equation modeling, multivariate statistics, and hierarchical linear modeling. Her research deals with the provision of equitable access to educational resources for all students, including linguistic and racial minority students.