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Context. Software Engineering (SE) has low female representation due togender bias that men are better at programming. Pair programming (PP) is commonin industry and can increase student interest in SE, especially women; but ifgender bias affects PP, it may discourage women from joining the field.  Objective. We explore gender bias in PP. In a remote setting where studentscannot see their peers' gender, we study how perceived productivity, technicalcompetency and collaboration/interaction behaviors of SE students vary byperceived gender of their remote partner.  Method. We developed an online PP platform (twincode) with a collaborativeediting window and a chat pane. Control group had no gender information abouttheir partner, while treatment group saw a gendered avatar as a man or woman.Avatar gender was swapped between tasks to analyze 45 variables oncollaborative coding behavior, chat utterances and questionnaire responses of46 pairs in original study at the University of Seville and 23 pairs in thereplication at the University of California, Berkeley.  Results. No significant effect of gender bias treatment or interactionbetween perceived partner's gender and subject's gender in any variable inoriginal study. In replication, significant effects with moderate to largesizes in four variables within experimental group comparing subjects' actionswhen partner was male vs female.

Exploring Gender Bias in Remote Pair Programming among Software Engineering Students: The twincode Original Study and First External Replication