Context. Software Engineering (SE) has low female representation due to gender bias that men are better at programming. Pair programming (PP) is common in industry and can increase student interest in SE, especially women; but if gender bias affects PP, it may discourage women from joining the field. Objective. We explore gender bias in PP. In a remote setting where students cannot see their peers' gender, we study how perceived productivity, technical competency and collaboration/interaction behaviors of SE students vary by perceived gender of their remote partner. Method. We developed an online PP platform (twincode) with a collaborative editing window and a chat pane. Control group had no gender information about their partner, while treatment group saw a gendered avatar as a man or woman. Avatar gender was swapped between tasks to analyze 45 variables on collaborative coding behavior, chat utterances and questionnaire responses of 46 pairs in original study at the University of Seville and 23 pairs in the replication at the University of California, Berkeley. Results. No significant effect of gender bias treatment or interaction between perceived partner's gender and subject's gender in any variable in original study. In replication, significant effects with moderate to large sizes in four variables within experimental group comparing subjects' actions when partner was male vs female.

翻译：背景. 软件工程领域女性代表性不足，部分归因于“男性更擅长编程”的性别偏见。结对编程在工业界普遍应用，能够提升学生对软件工程的兴趣，尤其对女生有利；但若性别偏见影响结对编程，则可能阻碍女性进入该领域。目的. 我们探索结对编程中的性别偏见。在远程环境中（学生无法看到同伴性别），研究软件工程学生的感知生产力、技术能力和协作/互动行为如何随远程同伴的感知性别而变化。方法. 我们开发了在线结对编程平台（twincode），包含协作编辑窗口和聊天面板。对照组无法获取同伴性别信息，实验组则看到代表男性或女性的性别化虚拟头像。各任务间切换头像性别，分析45个变量（涵盖协作编码行为、聊天话语及问卷反馈），原始研究于塞维利亚大学采集46对数据，复现研究于加州大学伯克利分校采集23对数据。结果. 原始研究中，性别偏见处理或同伴感知性别与受试者性别的交互作用在任何变量中均无显著效应。复现研究中，实验组内当同伴为男性与女性时，受试者行为在四个变量上出现中等至大效应的显著差异。