부산대학교 도서관

Since online discussion platforms can limit the perception of social cues, effective collaboration over videochat requires additional attention to conversational skills. However, self-affirmation and defensive bias theories indicate that feedback may appear confrontational, especially when users are not motivated to incorporate them. We develop a feedback chatbot that employs Motivational Interviewing (MI), a directive counseling method that encourages commitment to behavior change, with the end goal of improving the user's conversational skills. We conduct a within-subject study with 21 participants in 8 teams to evaluate our MI-agent 'MIA' and a non-MI-agent 'Roboto'. After interacting with an agent, participants are tasked with conversing over videochat to evaluate candidate résumés for a job circular. Our quantitative evaluation shows that the MI-agent effectively motivates users, improves their conversational skills, and is likable. Through a qualitative lens, we present the strategies and the cautions needed to fulfill individual and team goals during group discussions. Our findings reveal the potential of the MI technique to improve collaboration and provide examples of conversational tactics important for optimal discussion outcomes.