Many factors influence students’ confidence in their own computing abilities. CERP summarized the results of the Fall 2018 Data Buddies Survey (DBS) for Undergraduates to understand differences in confidence between student groups, particularly between students who are underrepresented in computing and students who are non-underrepresented in computing. A total of 7,808 undergraduate students responded to the Fall 2018 DBS survey and provided information about their race/ethnicity: 1,234 students who are underrepresented and 6,574 students who are non-underrepresented. All students were asked to respond to each of the items in this analysis on a scale of 1 (“Strongly disagree”) to 5 (“Strongly agree”).
Overall, all undergraduate students generally agree, with averages above 4.0 (“Somewhat agree”), they are confident that they will complete their undergraduate computing degree (M = 4.59, SD = 0.79), can learn computing concepts (M = 4.52, SD = 0.68), can pass their computing courses (M = 4.49, SD = 0.81), can find employment in the area of their computing interest (M = 4.28, SD = 0.87), and can communicate technical problems and solutions (M = 4.04, SD = 0.93). On average, undergraduates are least confident that they will do well in computing-related contests (M = 3.46, SD = 1.16) and that they will become a capable researcher in computing (M = 3.51, SD = 1.09).
Between students who are underrepresented and non-underrepresented, responses from students who are underrepresented indicate they are significantly more confident than non-underrepresented students that they will become capable researchers in computing, and that they will get admitted to a graduate computing program. Both of these results have an effect size greater than a Cohen’s d value of 0.15, demonstrating a modest effect. Results of the independent-samples t-tests conducted for these items are displayed in the Notes section below.
Students who are underrepresented indicate equal levels of confidence as their non-underrepresented peers that they will do well in a computing-related contest, that they can find employment in their area of computing interest, and that they can contribute to a computing research project.
Finally, although the following items reveal areas where responses from students who are underrepresented indicate significantly lower confidence than non-underrepresented peers, the minimal Cohen’s d effect size of these results indicates the significant differences may not be particularly meaningful. The items are: passing their computing courses (d = 0.13), learning foundations and concepts of computing (d = 0.07), quickly learning a new programming language on their own (d = 0.07), and completing an undergraduate degree in computing (d = 0.11).
Underrepresented is defined as students who are Black/African-American, Hispanic/Latinx, Indigenous/Native American, and/or Native Hawaiian/Other Pacific Islander.
Non-underrepresented is defined as students who are White/Caucasian and/or Asian.
Significant independent-samples t-tests at p < 0.05 and Cohen’s d >= 0.15:
- Underrepresented students responded with higher confidence (M = 3.71, SD = 1.10) than non-underrepresented students (M = 3.48, SD = 1.08) that they believe they can become capable researchers, t(1654) = -6.59, p < 0.001. Cohen’s d = 0.23
- Underrepresented students responded with higher confidence (M = 3.83, SD = 1.15) than non-underrepresented students (M = 3.74, SD = 1.10) that they believe they can get admitted to a graduate computing program, t(1628) = -2.65, p < 0.01. Cohen’s d = 0.17
The full-text of the ten survey questions appear below; they were abbreviated in the figure due to space constraints. “I am confident that I can…”
- do well in a computing-related contest (e.g., programming contest, robotics contest, hackathon)
- become a capable researcher in computing
- contribute to a research project in computing
- get admitted to a graduate computing program
- quickly learn a new programming language on my own
- clearly communicate technical problems and solutions to a range of audiences
- find employment in an area of computing interest
- pass my computing classes
- learn the foundations and concepts of computing
- complete an undergraduate degree in computing
This analysis is brought to you by the CRA’s Center for Evaluating the Research Pipeline (CERP). CERP provides social science research and comparative evaluation for the computing community. Subscribe to the CERP newsletter here. Volunteer for Data Buddies by signing-up here.
This material is based upon work supported by the National Science Foundation under grant numbers CNS-1246649, DUE-1431112, and/or DUE-1821136. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.