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Direct linkDana Kube; Joshua Weidlich; Karel Kreijns; Hendrik Drachsler – Education and Information Technologies, 2024
Gender bias underlying discrimination against women are particularly salient in STEM higher education. Complementing top-down measures to mitigate these issues identified in the extant literature, we aim to highlight a complementary bottom-up approach. First, to elicit gender stereotypes and gender bias in STEM, we conducted a group concept…
Descriptors: STEM Education, Gender Bias, Females, Scientists
Dana Kube; Sebastian Gombert; Nathalie John; Joshua Weidlich; Karel Kreijns; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Gender and gender diversity are group features affecting social interaction and are critical for gender-inclusive and equitable education. As such, the role of gender and gender diversity is of particular relevance to computer-supported collaborative learning (CSCL). However, up until now, research on this topic in CSCL remains scarce.…
Descriptors: Sexual Identity, Sex Role, Gender Differences, Gender Issues
Dana Kube; Sebastian Gombert; Brigitte Suter; Joshua Weidlich; Karel Kreijns; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Gender stereotypes about women and men are prevalent in computer science (CS). The study's goal was to investigate the role of gender bias in computer-supported collaborative learning (CSCL) in a CS context by elaborating on gendered experiences in the perception of individual and team performance in mixed-gender teams in a hackathon.…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Gender Issues, Learning Activities
