The main goal of e-learning systems is just-in-time knowledge acquisition. Rule-based elearning systems, however, suffer from the mesa effect and the cold start problem, which both result in low user acceptance. E-learning systems suffer a further drawback in rendering the implementation of a natural interface in humanoids difficult. To address these concerns, even exceptional questions of the learner must be answerable. This paper aims to propose a method that can understand the learner’s verbal cues and then intelligently explore additional domains of knowledge based on crowd data sources such as Wikipedia and social media, ultimately allowing for better answers in real-time. A prototype system was implemented using the NAO platform.

1. 서 론
 2. 관련 연구
 3. 로봇 기반 이러닝 시스템 제안
  3.1 시스템 개요
  3.2 규칙 베이스의 생성
  3.3 인간-로봇 인터페이스
  3.4 진행 방식
 4. 구 현
 5. 결 론
 References

• 권오병(The school of management, Kyung Hee University 26, Kyungheedae-ro, Dongdaemun-gu, Seoul, Korea) | Ohbyung Kwon Corresponding author
• 박필립(The school of management, Kyung Hee University) | Philip Park
• 김은지(The school of management, Kyung Hee University) | Eunji Kim