The Tech Trajectory: Examining the Role of College Environments in Shaping Students’ Interest in Computing Careers

Computing career opportunities are increasing across all sectors of the U.S. economy, yet there remains a serious shortage of college graduates to fill these jobs. This problem has fueled a nationwide effort to expand and diversify the computing career pipeline. Guided by social cognitive career theory (SCCT), this study used logistic regression to examine college students’ interest in a computing career and how that changes over time. Drawing from a multi-institutional, longitudinal sample of introductory computing course students, this study extends prior literature by examining a broad group of potential computing career aspirants (i.e., computing and non-computing majors). Results indicate that, two years after the introductory course, 53.5% of students indicated an interest in a computing career. Notably, this interest changed significantly over time, and our findings indicate that students in this sample were more likely to leave the computing career pipeline than to be recruited to it. Positive predictors of computing career interest include initial computing career interest, family support, and time spent in computing-related student groups. Additional positive predictors such as sense of belonging in computing and computing self-efficacy underscore the importance of psychosocial attributes in shaping this career interest. Beyond individual characteristics, this study reveals key areas where faculty and institutions can better address elements of the college experience to bolster students’ interest and confidence in pursuing computing careers. Implications for theory, research, and practice are discussed.

The Tech Trajectory: Examining the Role of College Environments in Shaping Students’ Interest in Computing Careers

  • Author George, Kari L. and Sax, Linda J. and Wofford, Annie M. and Sundar, Sarayu
  • Publication Title Research in Higher Education
  • Publication Year 2022
  • BPC Focus NA
  • Methodology Survey, Longitudinal, Multi-institution
  • Analytic Method Structural Equation Modeling (SEM), Chi-square/Contingency Table, Regression
  • Institution Type NA
  • DOI 10.1007/s11162-021-09671-7
  • URL https://doi.org/10.1007/s11162-021-09671-7