Connecting Math Attitudes With STEM Career Attainment: A Latent Class Analysis Approach
For many years now, there have been many job vacancies in science, technology, engineering, and mathematics (STEM), but not enough workers to fill these vacancies. Much attention has been given to understanding and changing this situation in our country. The purpose of this study is to address this dilemma by understanding what may be gained by investigating student’s attitudes towards STEM in high school. Specifically, we study the relationship between students’ math attitudes and math self-efficacy beliefs and their career outcomes in STEM. Further, we do this across different English proficiency levels to see if any understanding may be gained by studying these groups differently. This study implemented secondary analysis by using a nationally representative sample of U.S. 10th graders from the Education Longitudinal Study. A latent class analysis was used to classify students’ math attitudes and self-efficacy. The results from this study provide empirical support suggesting that across all three English proficiency groups, students with high math attitudes and high math self-efficacy were more likely to have a career in STEM. When examining demographic characteristics, female students were more likely to have lower math attitude and lower math self-efficacy, which helps to explain why there is an underrepresentation of female students in STEM fields. We also found that race/ethnicity and socioeconomic status operated differently for each of the English proficiency groups. This study directly links student math attitudes and self-efficacy to later career choice. This study has implications for researchers and policymakers who are developing interventions, suggesting that fostering positive math attitudes and self-efficacy would help encourage more students to pursue careers in STEM, particularly for non-native English speakers and female students.