Mining gender bias: A preliminary study on implicit biases and gender identity in the department of computer science at the technical university of munich

Ana Petrovska, Patricia Goldberg, Anne Brüggemann-Klein, Anne Nyokabi

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)

Abstract

The concept of implicit biases is widely seen in many different areas and is regarded as one of the main reasons for the gender disparity between students pursuing degrees in Computer Sciences. Since less than 20% of Computer Science students are female, the information about gender bias in this field is of extreme importance. This research aimed to investigate if and by how much the female students in our department are affected by likely gender bias in their academic life. The data collected in this research was used to evaluate the automatic association that students have towards a specific gender and the computer science field.

OriginalspracheEnglisch
TitelSoftware Architecture - 14th European Conference, ECSA 2020 Tracks and Workshops, Proceedings
Redakteure/-innenHenry Muccini, Mirco Franzago, Paris Avgeriou, Barbora Buhnova, Javier Camara, Mauro Caporuscio, Anne Koziolek, Patrizia Scandurra, Catia Trubiani, Danny Weyns, Uwe Zdun
Herausgeber (Verlag)Springer Science and Business Media Deutschland GmbH
Seiten138-150
Seitenumfang13
ISBN (Print)9783030591540
DOIs
PublikationsstatusVeröffentlicht - 2020
Veranstaltung14th European Conference on Software Architecture,ECSA 2020 - L'Aquila, Italien
Dauer: 14 Sept. 202018 Sept. 2020

Publikationsreihe

NameCommunications in Computer and Information Science
Band1269 CCIS
ISSN (Print)1865-0929
ISSN (elektronisch)1865-0937

Konferenz

Konferenz14th European Conference on Software Architecture,ECSA 2020
Land/GebietItalien
OrtL'Aquila
Zeitraum14/09/2018/09/20

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