@inproceedings{de393d92e8f147cd9131e0d7af3ac571,
title = "Mining gender bias: A preliminary study on implicit biases and gender identity in the department of computer science at the technical university of munich",
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.",
keywords = "Computer science, Gender bias, University and academia",
author = "Ana Petrovska and Patricia Goldberg and Anne Br{\"u}ggemann-Klein and Anne Nyokabi",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 14th European Conference on Software Architecture,ECSA 2020 ; Conference date: 14-09-2020 Through 18-09-2020",
year = "2020",
doi = "10.1007/978-3-030-59155-7_11",
language = "English",
isbn = "9783030591540",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "138--150",
editor = "Henry Muccini and Mirco Franzago and Paris Avgeriou and Barbora Buhnova and Javier Camara and Mauro Caporuscio and Anne Koziolek and Patrizia Scandurra and Catia Trubiani and Danny Weyns and Uwe Zdun",
booktitle = "Software Architecture - 14th European Conference, ECSA 2020 Tracks and Workshops, Proceedings",
}