“Taught to be automata”: Examining the departmental role in shaping initial career choices of computing students

ABSTRACT

Background and Context

Post-secondary Computer Science (CS) students’ career choices are complex sociocultural decisions, shaped by self-efficacy, belonging, and a multitude of known factors. Prior work has investigated the effect of these factors on career choice, but perspectives that examine norms of career practice are unexplored within computing.

Objective

This work applies Field Theory to surface the norms of career practice within a CS department, the mechanisms used to reinforce these norms, and students’ experience of these norms.

Method

We conducted semi-structured interviews of 18 students, graduates, academic advisors and senior faculty program leaders within one CS department, analyzing data with a Bourdieusian lens.

Findings

In line with prior work, we found that normative career practice centered prestige, leading students to prioritize work at elite technology companies. This work contributes three mechanisms of norm enforcement: companies utilized their departmental position to recruit more effectively, curricula optimized preparing students for prestigious work, and career advising assumed alignment with departmental norms. Students aligned with departmental norms opted for prestige to alleviate career uncertainty and because more fulfilling work felt inaccessible; students unaligned with departmental norms felt conflicted about their participation within CS and substantial effort was required to resist norms.

Implications

Normative CS career practice likely discourages students who lack alignment with norms from participating in CS; additionally, the narrowness of established norms leaves little space for alternatives. Broadening participation efforts in CS are unlikely to be successful without structurally broadening what constitutes legitimate career practice to make space for students’ diverseaspirations.

KEYWORDS:

• Careers
• norms
• advising
• post-secondary

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. For this work, we use “department” to refer to departments, schools, colleges, and other academic units.

2. We obtained approval from our university’s Institutional Review Board before beginning this work.

3. Unfortunately, existing data only asks about student plans, rather than where students actually end up.

4. https://www.reddit.com/r/cscareerquestions/.

Additional information

Funding

This material is based upon work supported by the National Science Foundation under Grant No. 1539179, 1703304, 1836813, 2031265, 2100296, 2122950, 2137834, 2137312, and unrestricted gifts from Microsoft, Adobe, and Google.

Notes on contributors

Mara Kirdani-Ryan

Mara Kirdani-Ryan is a PhD student at the Paul G. Allen School of Computer Science & Engineering at the University of Washington (Seattle, USA). Their research critically examines cultural norms in computer science and explores teaching those norms to others.

Amy J. Ko

Amy J. Ko is a Professor at the University of Washington Information School (Seattle, USA). She studies our individual and collective struggle to understand computing and harness it for equity and justice.

Emilia A. Borisova

Emilia A. Borisova is an undergraduate student at the Paul G. Allen School of Computer Science and Engineering at the University of Washington (Seattle, USA).