A hierarchical linear modeling approach to understanding the role of ethnicity and socioeconomic status on precollege engineering conceptions research to practice

Abstract

Traditional precollege formal education includes state and federal mandated science and mathematics content. Most recently standards also include engineering content to support initiatives that. prepare more of the American population for the engineering challenges of the future. This study focused on a precollege engineering education intervention. Potential interactions between student and school level factors and students' pre-test achievement were explored using a multilevel modeling data analysis approach (i.e. investigating students within schools). Findings suggest that the statistically significant predictors of the students' pre-test scores are school socioeconomic status and ethnicity. Students who attended a school with a higher proportion of students on free and reduced lunch (FRL) - where FRL is used as a measure of socio-economic status - on average have lower scores than those who attend schools with a lower proportion of FRL receiving students. The second finding is that on average, African American and Hispanic students earn fewer points on the pre-test than do students belonging to other ethnic groups. The findings further suggest that family and community knowledge can influence student knowledge and test scores. As engineering education researchers and practitioners, we must apply these insights to the ways that we engage with diverse students and to the design of our curricula.