Proficiency in Basic Data Structures among Various Subpopulations of Students at Different Stages in a CS Program (Best Paper Award Finalist)

Previous studies show that CS students may not learn as much from their courses as we might expect. This could have ramifications on how students succeed in their future careers and may explain why researchers report a gap between industry expectations and the abilities of recent CS graduates. However, previous studies have also shown that students improve their prerequisite knowledge in subsequent courses. This study investigates the introductory data structures proficiency of students in different courses at various stages in our CS program, employing the validated Basic Data Structures Inventory (BDSI). Additionally, we investigate whether subpopulations, including transfer students and underrepresented groups, may be more prone to not attaining as much knowledge from our courses as we might expect. We find that students’ knowledge of basic data structures is, on average, better in later courses. However, we also find subpopulations of students that perform worse than others or seem to not improve their knowledge in later courses. Specifically, we find students that transferred to our institution from a different school perform significantly worse on the BDSI than other students and do not improve their BDSI performance in later courses. We also find students from demographic backgrounds that are underrepresented in computing scored slightly, though not statistically significantly, worse than others. Our findings warrant future investigations on how our programs can better serve the students in the affected subpopulations.