표정 분석 데이터를 활용한 원격화상 토론 학습 지원전략 개발

Abstract

Objectives In order to develop the design principles for online discussion in videoconferencing instruction, this study develops the design principles by using learning analysis data analyzed with facial expression analysis tool and confirms the user's reaction.
 Methods Using the design and development research method, the initial design principles was developed by analyzing previous research and problems of videoconferencing classroom field. They were modified and developed through expert validation tests for three times. A prototype of facial expression analysis tool was developed to evaluate usability, and the final design principles were developed.
 Results The final support strategy consists of 9 support strategies and 26 detailed guidelines, tailored to the pre-debate, during the debate, and post-debate stages. In this regard, it has been confirmed by users that the strategy enables to simultaneously perceive non-verbal elements and to provide timely feedback. However, it was also observed that the intervention of instructors can function both as a strength and as a disruptive factor to discussions.
 Conclusions The above design principles are significant in that it suggested the prescription using learning analysis data what is facial expressions. It showed a new possibility to apply artificial intelligence technology at learning analysis by using facial expression analysis tool that automatically analyzes present a result value.