CRII: Cyberlearning: Teaching Intercultural Competence through Personal Informatics

随着技术使人们更容易参与全球交流、合作和商业，对跨文化能力的需求从未像现在这样高。在高等教育中，全球化和多元文化的环境意味着跨文化交流的挑战存在于课堂中。该项目将通过构建和测试名为CANAR（计算机辅助注意和反思）的软件，研究技术如何帮助STEM助教，特别是外国助教，更好地与跨文化的学生交流。最终目标是通过弥合学生和教师之间的文化鸿沟，在大学课堂上更好地教授和学习STEM。CANAR系统将使用迭代设计方法构建，并将建立在先前的个人信息学软件上，该软件使用接收者操作特征曲线下的面积（AUROC）对课堂环境中的语音进行说话者检测。这些数据将用于向助教展示一个基于Liddicoat的跨文化能力发展模型的仪表板。研究将使用定性观察和Corbin和Strauss的扎根理论方法来解决哪些数据和策略可以支持助教之间的跨文化注意和反思的问题，并检查这种反思对他们在课堂上的跨文化交际能力的好处。为了检验哪些类型的数据对跨文化能力有帮助，研究参与者将使用CANAR仪表板中的三种类型的数据：代表国际助教典型经验的人工合成数据，来自人类编码观察的参与者交流的真实数据，以及来自自动化系统的交流的真实数据。

The need for intercultural competence has never been higher as technology makes it easier for people to engage in global communications, collaboration, and commerce. In higher education, the global and multicultural environment means that the challenges of intercultural communication exist within classrooms. This project would study how technology can help STEM teaching assistants, especially foreign teaching assistants, better communicate with their students across cultural lines, by building and testing software called CANAR (Computer-Aided Noticing and Reflection). The ultimate goal is support better teaching and learning of STEM in university classrooms by bridging cultural divides between students and their teachers.The CANAR system will be constructed using an iterative design methodology, and will build on prior personal informatics software which uses the area under the receiver operating characteristics curve (AUROC) to do speaker-detection on speech in classroom settings. This data will be used to present TAs with a dashboard based on Liddicoat's model of developing intercultural competence. Research will be conducted using qualitative observation and Corbin and Strauss' approach to grounded theory to address questions of what data and strategies can support intercultural noticing and reflection among the TAs, and to examine the benefits of this reflection on their intercultural communication competencies in the classroom. To examine what types of data are helpful for intercultural competence, research participants will engage with three types of data in the CANAR dashboard: artificially synthesized data representing typical experiences by international TAs, real data on the participants' communication derived from human coded observations, and real data on the communication derived by the automated system.