Best Practices in Academia to Remedy Gender Bias in Tech Publikationsdatum:
Zu finden in: SIGCSE 2018 (Seite 672 bis 673), 2018
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Zusammenfassungen
The New York Times published an op-ed by Anita Hill [3] suggesting that women in tech consider class action to remedy the gender bias that is increasingly being reported in the mass-media. This panel raises the question "what are we doing in undergraduate programs to reduce the 'Mad Men', 'Brogrammer' culture she describes that is increasingly being reported in the popular press. Part of our mission as educators is to develop professional behavior so that our students entering the workforce not only understand what it means to act professionally, but understand that it is their responsibility to actively push back on the existing bias within the tech culture. As moderator Ursula Wolz brings a depth of insight from 40 years of industrial and academic experience, including a National Science Foundation project to broaden participation in computing [5]. She does not believe this problem can be solved through quantitative data collection on who does well in computer science, but that SIGCSE needs to begin to collect good stories (ala Sally Fincher [2]) on what constitute best practices to support diversity. The panelists present a range of perspectives that have the potential to establish new cultural norms in the single most influential industry in our economy.
Dieses Konferenz-Paper erwähnt ...
Personen KB IB clear | Carol Dweck , Paola Medel , Vahab Pournaghshband | |||||||||||||||||||||||||||
Begriffe KB IB clear | fixed mindsetfixed mindset , GenderGender , gender bias , growth mindsetgrowth mindset , Informatikcomputer science , Informatik-Didaktikdidactics of computer science , Informatik-Unterricht (Fachinformatik)Computer Science Education | |||||||||||||||||||||||||||
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Dieses Konferenz-Paper erwähnt vermutlich nicht ...
Nicht erwähnte Begriffe | Informatikunterricht in der Schule |
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Best Practices in Academia to Remedy Gender Bias in Tech: Fulltext at the ACM Digital Library (: , 563 kByte; : 2020-11-28) |
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