Need for Change: How Interview Preparation and the Hiring Process in Computing Can Be Made More Equitable

Stephanie Jill Lunn; Ellen Zerbe; Monique S Ross

Download Paper | Permalink

Conference: 2022 CoNECD (Collaborative Network for Engineering & Computing Diversity)
Location: New Orleans, Louisiana
Publication Date: February 20, 2022
Start Date: February 20, 2022
End Date: July 20, 2022
Conference Session: Technical Session 2 - Paper 5: Need for Change: How Interview Preparation and the Hiring Process in Computing Can Be Made More Equitable
Tagged Topics: Diversity and CoNECD Paper Sessions
Page Count: 25
DOI: 10.18260/1-2--39131
Permanent URL: https://peer.asee.org/39131
Download Count: 478

Paper Authors

biography

Stephanie Jill Lunn Georgia Institute of Technology orcid.org/0000-0003-3840-1822

visit author page

Stephanie Lunn is presently a postdoctoral fellow in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Institute of Technology and Emory University. She recently completed her Ph.D. from the Knight Foundation School of Computing and Information Sciences at Florida International University (FIU). Her research interests span the fields of Computing and Engineering Education, Human Computer Interaction, Data Science, and Machine Learning. Previously, Stephanie received her B.S. and M.S. degrees in Neuroscience from the University of Miami, in addition to B.S. and M.S. degrees in Computer Science from FIU.

visit author page

biography

Ellen Zerbe Pennsylvania State University

visit author page

Ellen Zerbe is a graduate student pursuing a Ph.D. in Mechanical Engineering at Pennsylvania State University. She earned her B.S.M.E. at Grove City College. She is currently researching under Dr. Catherine Berdanier in the Engineering Cognition Research Laboratory.

visit author page

biography

Monique S Ross Florida International University orcid.org/0000-0002-6320-636X

visit author page

Monique Ross, Assistant Professor in the School of Computing and Information Sciences and STEM Transformation Institute at Florida International Her research interests include broadening participation in computing through the exploration of: 1) race, gender, and identity in the academy and industry; 2) discipline-based education research in order to inform pedagogical practices that garner interest and retain women and minorities in computer-related engineering fields. She uses her scholarship to challenge the perceptions of who belong in computing.

visit author page

Download Paper | Permalink

Abstract

Media and literature frequently describe the need to increase the number of workers in computing to meet growing demands and highlight the necessity of broadening participation. Although companies may claim they want to do better, and some have begun to develop and implement initiatives to promote and improve diversity, ongoing reports of discrimination and metrics demonstrate there is still a long way to go to achieve inclusivity and parity in representation, particularly for women, Hispanic/Latinx, and Black/African American workers. To learn more about students’ pathways to a career, especially those which are underrepresented in the discipline, and to examine what they believe may ameliorate interview preparation and the hiring process, we employed phenomenography. Phenomenography has been used in computing and engineering education as a qualitative methodology to assess how people may experience and conceptualize phenomena. This inquiry applied the theoretical framework of intersectionality to examine the experiences of minoritized undergraduate computing students and their pathways to job attainment, and to learn about what may help to improve the process. Specifically, the investigation was guided by the research question: What do students feel would help to improve hiring in computing? The participants included 16 students in computing, all of whom had completed at least one technical interview and received at least one job offer. The goal in phenomenographic data analysis is to develop an outcome space — the visual representation of a hierarchical set of distinct, but logically related, categories. From the analysis, an outcome space emerged with five main categories of description about the kinds of obstacles students encountered in regard to the hiring process in computing and industry practices: Uncertainty, interview techniques, time demands of preparation, anxiety management, and improving inclusivity. Yet, our goal was not to focus on the issues faced, but the solutions to resolve them. As such, the perceptions of the students’ experiences guided the creation of a set of recommendations for students, academia, and industry, to mitigate concerns with the current process and to consider avenues for improvement.

Citation
Format

Lunn, S. J., & Zerbe, E., & Ross, M. S. (2022, February), Need for Change: How Interview Preparation and the Hiring Process in Computing Can Be Made More Equitable Paper presented at 2022 CoNECD (Collaborative Network for Engineering & Computing Diversity) , New Orleans, Louisiana. 10.18260/1-2--39131

TY  - CPAPER
AB  - Media and literature frequently describe the need to increase the number of workers in computing to meet growing demands and highlight the necessity of broadening participation. Although companies may claim they want to do better, and some have begun to develop and implement initiatives to promote and improve diversity, ongoing reports of discrimination and metrics demonstrate there is still a long way to go to achieve inclusivity and parity in representation, particularly for women, Hispanic/Latinx, and Black/African American workers. To learn more about students’ pathways to a career, especially those which are underrepresented in the discipline, and to examine what they believe may ameliorate interview preparation and the hiring process, we employed phenomenography. Phenomenography has been used in computing and engineering education as a qualitative methodology to assess how people may experience and conceptualize phenomena. This inquiry applied the theoretical framework of intersectionality to examine the experiences of minoritized undergraduate computing students and their pathways to job attainment, and to learn about what may help to improve the process. Specifically, the investigation was guided by the research question: What do students feel would help to improve hiring in computing? The participants included 16 students in computing, all of whom had completed at least one technical interview and received at least one job offer. The goal in phenomenographic data analysis is to develop an outcome space — the visual representation of a hierarchical set of distinct, but logically related, categories. From the analysis, an outcome space emerged with five main categories of description about the kinds of obstacles students encountered in regard to the hiring process in computing and industry practices: Uncertainty, interview techniques, time demands of preparation, anxiety management, and improving inclusivity. Yet, our goal was not to focus on the issues faced, but the solutions to resolve them. As such, the perceptions of the students’ experiences guided the creation of a set of recommendations for students, academia, and industry, to mitigate concerns with the current process and to consider avenues for improvement.
AU  - Stephanie Jill Lunn
AU  - Ellen Zerbe
AU  - Monique S Ross
CY  - New Orleans, Louisiana
DA  - 2022/02/20
PB  - ASEE Conferences
TI  - Need for Change: How Interview Preparation and the Hiring Process in Computing Can Be Made More Equitable
UR  - https://peer.asee.org/39131
DO  - 10.18260/1-2--39131
ER  -