New Publication: Addressing gender in STEM classrooms: The impact of gender bias on women scientists’ experiences in higher education careers in Germany

New Publication: Addressing gender in STEM classrooms: The impact of gender bias on women scientists’ experiences in higher education careers in Germany

New Pub
 In an expert study conducted in Germany, Dana Kube and her research team delve into the complex dynamics of gender bias within STEM (Science, Technology, Engineering, and Mathematics) classrooms. The study, aimed at understanding the role gender plays in shaping the experiences of women scientists in higher education, sheds light on the challenges they face and proposes strategies for fostering gender inclusivity in STEM classrooms. The primary objective of the study was two-fold: first, to comprehensively examine the influence of gender and gender bias in STEM environments within higher education institutions, and second, to identify potential areas where Computer-Supported Collaborative Learning (CSCL) pedagogical interventions could mitigate these biases among students and teachers in German STEM departments. Employing the innovative group concept mapping method, the research team collaborated with women participants…
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Unveiling Gender Bias in Computer-Supported Collaborative Learning: Insights from a CS Hackathon Study

Unveiling Gender Bias in Computer-Supported Collaborative Learning: Insights from a CS Hackathon Study

Computer-supported collaborative learning, Digitalisation, Event, Gender, Higher Education, Journal, Learning Design, New Pub, Open access, Publication, Research topic
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), group work in a CS context, by elaborating on gendered experiences in the perception of individual and team performance in mixed-gender teams in a hackathon. We applied an exploratory mixed-method approach using quantitative survey data, including collective self-esteem scales, at several time points during the hackathon, which was analysed with clustering and descriptive statistics and complemented with qualitative coding of interviews with participants. The Figure shows that, for both clusters, the self-esteem scores are predominantly located in the upper half of the scale, indicating a generally high (collective) self-esteem among all our participants. Nonetheless, all respective scores were lower for the women-dominated…
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