The research proposes to integrate theories and methods from computer-supported collaborative work and learning (CSCW and CSCL) to promote better human-computer intercultural interactions. The research will consist of three phases: 1) identify and categorize intercultural communication problems and determine how they impact group outcomes; 2) apply machine learning to automatically recognize recognize when communication problems arise (or are likely to arise); and, 3) develop and test interventions for improving intercultural communication that could be triggered based on the automatic analysis.
This work has the potential to improve the design of global on-line classroom experiences and business collaborations. At the societal level, the research will help improve intercultural communication and the effectiveness of intercultural teams. This work will also advance the emerging field of automatic collaborative process analysis, which until now has focused only on English-speaking collaborations.
The research seeks to integrate theories and methods from computer-supported collaborative work and learning (CSCW and CSCL) to promote better human-computer intercultural interactions. The research has three major goals: 1) identify and categorize intercultural communication problems and determine how they impact group outcomes; 2) apply machine learning to automatically recognize when communication problems arise (or are likely to arise); and, 3) develop and test interventions for improving intercultural communication that could be triggered based on the automatic analysis. Intellectual merit: The project provides unique contribution in four areas: (a) providing a new integration of theories and methods from the fields of CSCW and CSCL that advances both areas individually and, together, human-computer interaction as a whole; (b) developing the basic theory in CMC and related disciplines by identifying how cultural differences due to gender and communication medium can give rise to communication problems that in turn lead to poor team outcomes: (c) developing the basic theory in CSCL by extending the concept of transactivity to non-educational task domains and non-Western cultural contexts and by advancing knowledge about how dynamic interventions interact with cultural variables and thus might differently affect participants from Western versus Asian cultures. (d) advancing theories and methods of text classification particularly in the emerging area of social media by revealing patterns of linguistic features that are predictive of transactive conversational moves in non-native English. Broader impact: This project has the potential to improve the design of global on-line classroom experiences and business collaborations. It integrated diversity into research activities and broadened participation of underrepresented groups by establishing research and education collaborations with graduate students who are women and members of underrepresented minority groups. At the societal level, the research will help improve intercultural communication and the effectiveness of intercultural teams. This work will also advance the emerging field of automatic collaborative process analysis, which until now has focused only on English-speaking collaborations. This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
