High School Students’ Perceptions of and Attitudes Towards R Programming in Statistics and Data Science

This study explores high school students’ (n = 313) perceptions of and attitudes towards R programming in statistics and data science courses that use the CourseKata curriculum, which integrates R coding within an interactive statistics textbook. Specifically, we explore (a) shifts in confidence, positive sentiment, anxiety, perceived difficulty, and enjoyment from the beginning to the end of the course, (b) the predictive relationships between students’ attitudes toward R programming and their future interest in statistics and data science, and whether there are differential patterns by racially marginalized background (including Black, Latine, and other racially marginalized groups). Findings reveal positive shifts in students' confidence and sentiment, coupled with reductions in anxiety and perceived difficulty. For perceived difficulty, racially marginalized students showed less pronounced declines over time compared to non-marginalized students. Predictive analyses highlight that post-course confidence and enjoyment in learning R strongly predict future interest in statistics, particularly for racially marginalized students. These findings underscore the potential of integrated R programming curricula to foster positive attitudes toward coding, while also emphasizing the need to address equity gaps in students’ experiences.