June 15, 2019
June 15, 2019
October 19, 2019
Electrical and Computer
Over the past 30 years, students of color have been underrepresented among students completing computer science and computer engineering undergraduate degrees. While we do not directly control the rate at which students apply and are accepted at our institutions, we should strive to create environments that are conducive to URM student success once they are accepted.
A five year program is aimed at increasing the enrollment and graduation rates of women and underrepresented minority (URM) students in computer science and engineering at a competitive public research institution. Three obstacles to diversity in computer science and computer engineering have been identified: stereotyped traits, perceived abilities, and learning environment. Identifying implicit bias and imposter syndrome as components of these obstacles, we include a series of class 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.
Previously, we investigated the difference between men’s and women’s perceptions of their abilities and the learning environments in introductory computing courses. We found a statistically significant association between gender and perception of self-efficacy, but not in how those perceptions change over the course of the term. In this paper, we expand our analysis to examine the experience of URM compared to non-URM students.
Our research question is: Are URM students associated with different perceptions of their abilities and learning environment as measured by confidence in success, intimidation by programming, and feelings of inclusion?
Our data set is comprised of entry and exit survey data for three semesters of introductory computing courses. The survey data will be analyzed using mixed model ANOVA for repeated measures of questions on self-efficacy, intimidation by programming, and feelings of inclusion. The results and analysis will be presented in this paper.
Alford, L. K., & Deorio, A. (2019, June), Student Perceptions of Their Abilities and Learning Environment in Large Introductory Computer Programming Courses - Underrepresented Minorities Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--33297
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2019 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015