A Demographic Analysis on Prerequisite Preparation in an Advanced Data Structures Course
Previous work in computing has shown that Black, Latinx, Native American and Pacific islanders (BLNPI), women, first-generation, and transfer students tend to have worse outcomes during their time in university compared to their majority counterparts. Previous work has also found that students’ incoming prerequisite course proficiency is positively correlated with their outcomes in a course. In this work, we investigate the role that prerequisite course proficiency has on outcomes between these groups of students. Specifically, we examine incoming prerequisite course proficiency in an Advanced Data Structures course. When comparing incoming prerequisite course proficiency between demographic pairs, we only see small differences for gender or by first-generation status. There is a sizeable difference by BLNPI status, although this difference is not statistically significant, possibly due to the small number of BLNPI students. In addition, we find that transfer students have sizeable and statistically significantly lower prerequisite course proficiency when compared to nontransfer students. For BLNPI and transfer students, we find that they also have lower grades in the prerequisite courses, which may partially explain their lower prerequisite course proficiency. These findings suggest that institutions need to find ways to better serve BLNPI and transfer students.
A Demographic Analysis on Prerequisite Preparation in an Advanced Data Structures Course
- Author Krause-Levy, Sophia; Valstar, Sander; Porter, Leo; Griswold, William G
- Publication Year 2022
- BPC Focus Gender, Underrepresented Racial/Ethnic Groups, Black/African American Students, Latinx/Hispanic, Native American Students, Native Hawaiian/Pacific Islander Students, First-generation Students
- Methodology NA
- Analytic Method T-test, ANOVA, Correlation
- Institution Type NA
- DOI 10.1145/3534563
- URL https://doi.org/10.1145/3534563