From Gender Biases to Gender-Inclusive Design

Vorvoreanu, Mihaela; Zhang, Lingyi; Huang, Yunhan; Hilderbrand, Claudia; Steine-Hanson, Zoe; Burnett, Margaret

doi:10.1145/3290605.3300283

Cited by 86 publications

(58 citation statements)

References 50 publications

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“…Previous work has found that gender differences are likely in problem-solving activities, including programming [4,90,100]. Sharafi et al [86] also reported different attention distribution trends based on gender and showed that women participants pay more attention to analyzing and ruling out wrong identifiers.…”

Section: Rq3 -Visual Attention Differencesmentioning

confidence: 98%

Biases and differences in code review using medical imaging and eye-tracking: genders, humans, and machines

Huang

Leach

Sharafi

et al. 2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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Code review is a critical step in modern software quality assurance, yet it is vulnerable to human biases. Previous studies have clarified the extent of the problem, particularly regarding biases against the authors of code, but no consensus understanding has emerged. Advances in medical imaging are increasingly applied to software engineering, supporting grounded neurobiological explorations of computing activities, including the review, reading, and writing of source code. In this paper, we present the results of a controlled experiment using both medical imaging and also eye tracking to investigate the neurological correlates of biases and differences between genders of humans and machines (e.g., automated program repair tools) in code review. We find that men and women conduct code reviews differently, in ways that are measurable and supported by behavioral, eye-tracking and medical imaging data. We also find biases in how humans review code as a function of its apparent author, when controlling for code quality. In addition to advancing our fundamental understanding of how cognitive biases relate to the code review process, the results may inform subsequent training and tool design to reduce bias. CCS CONCEPTS • Software and its engineering → Collaboration in software development; • Human-centered computing → Empirical studies in collaborative and social computing.

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Section: Rq3 -Visual Attention Differencesmentioning

confidence: 98%

Biases and differences in code review using medical imaging and eye-tracking: genders, humans, and machines

Huang

Leach

Sharafi

et al. 2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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“…Researchers have explored how to improve women's participation in SE education, open source development, and the professional labor market. For example, researchers at Oregon State Universities proposed the GenderMag approach to improving the gender inclusiveness in end-user development [9,52,79]. Fairness testing, though not only focusing on gender equality, provides a unified framework to detect and test software systems for potential discriminations, including that against females [30].…”

Section: Gender Issues In Software Engineeringmentioning

confidence: 99%

Reducing implicit gender biases in software development: does intergroup contact theory work?

Wang¹,

Zhang

2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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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. CCS CONCEPTS • Social and professional topics → Women; • Human-centered computing → Empirical studies in collaborative and social computing.

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“…It consists of a specialized cognitive walkthrough and a set of personas structured around five underlying gender differences in technology use (see Sections 2.4, 2.5, 2.6), offering HCI designers step-by-step how-to guides and ready-to-use forms to uncover and document gender barriers in existing systems [33,56,144,182]. Recent work has also shown its promise as a design aid [211] (Figure 4.1).…”

Section: Gender-inclusive Designmentioning

confidence: 99%

Gender-Inclusive HCI Research and Design: A Conceptual Review

Stumpf¹,

Peters²,

Bardzell³

et al. 2020

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Previous research has investigated gender and its implications for HCI. We consider inclusive design of technology whatever the gender of its users of particular importance. This conceptual review provides an overview of the motivations that have driven research in gender and inclusive HCI design. We review the empirical evidence for the impact of gender in thinking and behavior which underlies HCI research and design. We then present how HCI design might inadvertently embed and perpetuate gender stereotypes. We then present current HCI design approaches to tackle gender stereotypes and to produce gender-inclusive designs. We conclude by discussing possible future directions in this area.

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From Gender Biases to Gender-Inclusive Design

Cited by 86 publications

References 50 publications

Biases and differences in code review using medical imaging and eye-tracking: genders, humans, and machines

Biases and differences in code review using medical imaging and eye-tracking: genders, humans, and machines

Reducing implicit gender biases in software development: does intergroup contact theory work?

Gender-Inclusive HCI Research and Design: A Conceptual Review

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