PI: Amy Ogan
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.