@inproceedings{vorvoreanu2019from,
author = {Vorvoreanu, Mihaela and Zhang, Lingyi and Huang, Yun-Han and Hilderbrand, Claudia and Steine-Hanson, Zoe and Burnett, Margaret},
title = {From Gender Biases to Gender-Inclusive Design: An Empirical Investigation},
organization = {ACM},
booktitle = {Conference on Human Factors in Computing Systems (CHI 2019)},
year = {2019},
month = {May},
abstract = {In recent years, research has revealed gender biases in numerous software products. But although some researchers have found ways to improve gender participation in specific software projects, general methods focus mainly on detecting gender biases—not fixing them. To help fill this gap, we investigated whether the GenderMag bias detection method can lead directly to designs with fewer gender biases. In our 3-step investigation, two HCI researchers analyzed an industrial software product using GenderMag; we derived design changes to the product using the biases they found; and ran an empirical study of participants using the original product versus the new version. The results showed that using the method in this way did improve the software’s inclusiveness: women succeeded more often in the new version than in the original; men’s success rates improved too; and the gender gap entirely disappeared.},
url = {http://approjects.co.za/?big=en-us/research/publication/from-gender-biases-to-gender-inclusive-design-an-empirical-investigation/},
}