Interaction effects of race and gender in elementary CS attitudes: A validation and cross-sectional study

Abstract

Abstract Computer science (CS) initiatives for elementary students, including brief Hour of Code activities and longer in- and after-school programs that emphasize robotics and coding, have continued to increase in popularity. Many of these initiatives are intended to increase CS exposure to students who historically have been underrepresented in CS academic trajectories, including women and students of color. This study aimed at examining the gender and race difference in elementary students’ attitudes towards CS. To that end we developed and validated a survey instrument called Elementary Computer Science Attitudes (E-CSA) which consisted of the constructs of CS self-efficacy and outcome expectancy, through a combination of classical test theory and item response theory. The target audience for this instrument and study was upper elementary students (grades 4 and 5, ages 8 to 11). The E-CSA was found to be a gender and race bias-free instrument. A two-way ANOVA test was then used to answer research questions. We found no significant interaction effect between gender and race in the two constructs of CS Attitudes. We also did not see a significant difference based on race. However, a significant difference was found in both CS attitudes constructs based on gender, whereby male students had higher CS attitudes than female students. We discuss our findings from the perspective of the equity issue in CS education. Furthermore, we believe the E-CSA instrument can inform classroom-based interventions, the development of curricular materials, and reinforce findings from cross-sectional CS studies.