Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A study on the Change of University Education Based on Fliped Learning Using AI

AI 쳇봇을 활용한 플립러닝 기반의 대학교육의 변화

  • Kim, Ock-boon (Center for Teaching and Learning, Daejeon University) ;
  • Cho, Young-bok (Department of Information Security, Daejeon University)
  • Received : 2018.08.22
  • Accepted : 2018.09.26
  • Published : 2018.12.31
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Abstract

The undergraduate structure based on flipped learning should be a necessary course to cultivate value creation capability based on students' problem solving capability through the change of university education in the fourth industrial revolution era. Flipped learning stimulated the learner's high order thinking and activates communication between the faculty-student and the students through the use of activity oriented teaching strategy. Introduction and spread of Flipping Learning combining project-based learning with MOOC is required. The professor should be able to apply net teaching and learning methods using flipping learning and active learning, and develop class contents reflecting new knowledge, information and technology. As the introduction and spread of AI-based(E-Advisor, chat bot et al) learning consulting, Which is becoming increasingly advanced, the transition to "personalized education" that meets the 4th Industrial Revolution should be made.

플립러닝을 기반으로 학부중심 학사 구조가 4차 산업혁명시대 대학교육의 변화를 통해 학생들은 문제 해결능력을 기반으로 가치창출 능력을 배양하는 필수화 과정이 되어야 한다. 이를 위해 창안된 프로젝트기반 학습법(Project Based Learning)과 MOOC를 결합한 거꾸로 학습법(Flipped Learning)을 과감하게 도입 및 확산하고, 날로 고도화되어 가는 AI기반의 학습컨설팅(E-Advisor)의 도입과 확산에 따라 4차 산업혁명에 부합하는 "개인 맞춤교육"으로의 전환이 이루어져야 한다.

Keywords

HOJBC0_2018_v22n12_1618_f0001.png 이미지

Fig. 1 Bot connection method for AI utilization.

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Fig. 2 Direct Line API Connection

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Fig. 3 Responding to GET requests with watermark values for query strings.

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Fig. 4 Message Activity

HOJBC0_2018_v22n12_1618_f0005.png 이미지

Fig. 5 Seq2Seq model

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Fig. 6 RNN/ChatBot/model.py

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Fig. 7 Chat Bot example screen

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