Reducing implicit gender biases in software development: does intergroup contact theory work?
Yi Wang, Min Zhang
Abstract
The software development profession suffers from severe gender biases, which could be explicit and implicit. However, SE literature has not systematically explored and evaluated the methods for reducing gender biases, especially for implicit gender biases. This paper reports on a field experiment to examine whether the intergroup contact theory could reduce implicit gender biases in software development. In the field experiment, 280 undergraduate students taking a project-centric introductory software engineering course were assigned to 70 teams with different contact configurations. We measured and compared their explicit and implicit gender biases before and after contacts in their teams. The study yields a rich set of findings. First, we confirmed the positive effects of intergroup contact theory in reducing gender biases, particularly the implicit gender biases in both general and SE-specific contexts. We further revealed that such effects were subjected to different contact configurations. The intergroup contact theory's effects were maximized in teams where the number of females is greater than or equal to the number of males. When the female is the minority group in a team, contacts among members contribute to reducing male members' implicit gender biases but fail to result in the same scale of effects on female members' implicit gender biases. The findings provide insights into using intergroup contact theory in reducing implicit gender biases in software development contexts.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get 7ccaa2b7-7b8e-4f04-acff-864fd3bc75bbCited by top-tier papers1
Ask how each one uses itRelated papers
- The Sound of Support: Gendered Voice Agent as Support to Minority Teammates in Gender-Imbalanced TeamAngel Hsing-Chi Hwang, Andrea Stevenson WonCHI 2024 · 9 citations
- Using Intersectional Representation & Embodied Identification in Standard Video Game Play to Reduce Societal BiasesMarie A. Jarrell, Reza Ghaiumy Anaraky, Bart P. Knijnenburg, Erin AshCHI 2021 · 17 citations
- Engineering gender-inclusivity into software: ten teams' tales from the trenchesClaudia Hilderbrand, Christopher Perdriau, Lara Letaw, Jillian Emard et al.ICSE 2020 · 32 citations
- Building and Sustaining Ethnically, Racially, and Gender Diverse Software Engineering Teams: A Study at GoogleElla Dagan, Anita Sarma, Alison Chang, Sarah D'Angelo et al.FSE 2023 · 22 citations
- The Effect of Gender De-biased Recommendations - A User Study on Gender-specific PreferencesThorsten Krause, Lorena Göritz, Robin GratzCHI 2025 · 3 citations
