Student Perceptions of Their Abilities and Learning Environment in Large Introductory Computer Programming Courses

Historically, institutions have struggled to increase the number of underrepresented minority (URM) students completing computer science and computer engineering undergraduate degrees. There are many potential obstacles to student success. Faculty that teach the large programming courses at our university identified three particular obstacles to diversity in computer science and computer engineering: stereotyped traits, perceived abilities, and learning environment. Identifying implicit bias and imposter syndrome as components of these obstacles, we implemented a series of activities designed to lessen the impact of implicit bias and imposter syndrome on our students in large-enrollment introductory computer programming courses. One element of assessing the success of our program is to use entry and exit surveys to gauge the change in students’ perceptions of their abilities and learning environment. In particular, we are interested in the difference between URM students’ and non-URM students’ perceptions of their abilities and the learning environments in these courses. In the present study, our overarching research question is: Do underrepresented students and non-underrepresented students show a statistically significant difference in their perceptions of their abilities and learning environment as measured by self-efficacy, intimidation by programming, and feelings of inclusion? This paper presents entry and exit survey results from three semesters (Fall 2017, Winter 2018, and Fall 2018) of two successive programming courses. The results were analyzed using mixed model ANOVA for repeated measures of questions on self-efficacy, intimidation by programming, and feelings of inclusion. Statistically significant results include: We observed a decrease in self-efficacy during the term for both courses in our study, although the effect is small and the decrease is slightly larger for URM students than non-URM students in Course 1; and a decrease in inclusion for students in Course 1, though again the effect is small. Overall, the perceptions of URM students are similar to non-URM students. Introduction and Motivation A recent survey by the National Science Foundation showed that higher education is still struggling to increase the number of underrepresented minority (URM) students completing computer science and computer engineering undergraduate degrees1. The reasons for this URM gap are complex, but they can be generalized into the problems of recruitment and retention. Recruiting URM students to computer computer science and computer engineering can be difficult because high school students have preconceptions ideas about who does – and does not – go into computer science and computer engineering.2 Retaining URM students can be challenging because it involves the behaviors and attitudes of many different instructors and hundreds or thousands of classmates.3,4 There are many potential obstacles to recruiting and retaining URM students, and ultimately these obstacles are also obstacles to individual student success in computer science and computer engineering. Faculty that teach the large programming courses at our university identified three particular obstacles to diversity in computer science and computer engineering: stereotyped traits,5 perceived abilities,6 and learning environment.7,8 Identifying implicit bias and imposter syndrome as components of these obstacles, we implemented a series of activities designed to lessen the impact of implicit bias and imposter syndrome on our students in large-enrollment introductory computer programming courses. Interventions implemented in the first and second programming courses include: • balanced teaching staff in terms of gender and race (visual representation is critical) • staff training on implicit bias, imposter syndrome, and stereotype threat • student activities related to implicit bias and imposter syndrome • personalized messaging via an electronic coaching system Our previous work9 looked at ways to remove or minimize the impact of three obstacles to diversity in the computer science and computer engineering undergraduate programs: stereotyped traits, perceived abilities, and learning environment. Originally, the study was focused on obstacles to gender diversity, but these obstacles exist for many different social groups. These introductory programming courses are some of the largest engineering classes offered at this institution; as such, they have a wide sphere of influence on the student body. An improved understanding of student experiences in these classes will provide guidance on creating and sustaining a welcoming environment for all students. Therefore, we embarked on a 5 year program to gather data and assess the differences in student perceptions in the large programming courses offered at our institution. Our initial analysis of gender differences in student perceptions of the impact of stereotypes, preconceived notions of ability, and learning environment on their experiences in their programming courses showed that there was a statistically significant difference between men and women’s perceptions, though the overall differences were small.10 We turn now to comparing the responses of underrepresented minority (URM) students vs. non-URM students. Recruiting and retaining underrepresented minorities requires term-by-term assessment of students’ perceptions of the courses. In particular, we chose to focus on indicators for self-efficacy, intimidation by programming, and inclusion. This paper details the entry and exit survey questions used to gather data for these indicators, the analysis results, and our comments on the comparisons between URM and non-URM students at the beginning of the term and at end of the term.