DOI QR코드

DOI QR Code

Policy and Strategy for Intelligence Information Education and Technology

지능정보 교육과 기술 지원 정책 및 전략

  • 이태규 (원광대학교 바이오나노화학부) ;
  • 정대철 (원광대학교 전기공학과) ;
  • 김용갑 (원광대학교 정보통신공학과)
  • Received : 2017.05.22
  • Accepted : 2017.06.29
  • Published : 2017.08.31

Abstract

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.

최근 지속적으로 논의하고 있는 '지능정보사회'란? 지능정보기술을 기반으로 사회 전 영역에서 인간능력의 한계를 뛰어넘는 자동화가 보편화된 미래사회상을 의미한다. 특히, 인간의 개입을 최소화하고, 데이터(또는 빅데이터) 기반 완전 자동화로의 진화를 지속적으로 추구하는 개념이다. 예를 들어, 자율형자동화는 인공지능을 핵심요소로 무인자동차를 지속적으로 지향하고 있다. 그러나 지금까지의 지능정보 연구는 지능화 자체를 중심으로 지능화 논리를 고도화하여, 인간의 뇌와 지능을 대체하고자 하는 노력을 기울여 왔다. 또한, 다른 한편으로 인간의 노동력을 대체하기 위해서 노동자의 작업 원리를 분석하여 최적화된 단순논리를 개발하여 노동자를 로봇으로 대체하려는 노력을 지속해왔다. 본 연구는 지능정보기술 연구 전략 및 교육서비스에 관한 접근전략, 교육방법, 세부정책 로드맵 등을 제안하여, 지능정보 교육 정책 및 지능정보기술 연구 전략을 시행하는데 중요한 기준과 방향을 제시하고자 한다. 특히, 교육방법으로 기초지능교육, 지능콘텐츠교육, 지능응용교육 등의 지능정보교육의 단계적 접근 방안을 제시한다. 또한, 지능화 및 자동화가 중심이 되는 4차 산업혁명 성패를 가를 수 있는 중요한 요소로서 지능정보기술, 지능교육콘텐츠, 지능형 교육시스템 개선을 위한 교육정책 방안을 제안한다.

Keywords

References

  1. Jung Eun Park, Sung-tak Oh, Kyu Yeop Lee, Chang Wan Woo, and Young-Wha Kim, "100 Policies of the Fourth Industrial Revolution and the Intelligent Information Society," Policy Planning Team, Korea Information Society Agency, 2017.
  2. Jae-yi Lee, "Alpha Going, Future Already," Mechanical Journal, Vol.56, No.8, pp.22-24, 2016.
  3. Seung-hwan Kim, "Future Education Policy Direction and Tasks of Intelligence Information Society," Education Policy Forum, Korea Education Research Association (KERA), pp. 49-53, 2016.
  4. Chang Soo Nam, Sung-Phil Kim, Dean Krusienki, and Anton Nijholt, "Research and Development in Brain-Computer Interfacing Technology: A Comprehensive Technical Review," Korean-American Scientists and Engineers Association (KSEA), Dec., 2015.
  5. Byung-Woon Kim, "Artificial Intelligence Policy Issue of the Fourth Industrial Revolution Period," Fourth Industrial Revolution and Bio (1st), Biotech Policy Research Center, Korea Research Institute of Bioscience & Biotechnology (KRIBB), BioINpro, Vol.34, 2017.
  6. "Intelligent information society mid-long term comprehensive measures in response to the Fourth Industrial Revolution," Ministry of Science, ICT and Future Planning (Joint ministry), 2016.
  7. Jin-hyun Jung, "Nine National Strategic Projects in Korea," The 2nd Science and Technology Strategy Conference, Ministry of Science, ICT and Future Planning, Science and Technology Innovation Team, 2016.
  8. Dong Yub Lee, "Research on Developing Instructional Design Models for Flipped Learning," The Journal of Digital Policy & Management, Vol.11, No.12, pp.83-92, 2013.
  9. Kil-Mo Kim and Seong-Sik Kim, "Development of a PBL-based Programming Instruction Model Using Collective Intelligence," The Journal of Korean Association of Computer Education, Vol.14, No.2, pp.23-32, 2011.
  10. Jin-ha Kim, "The Fourth Industrial Revolution, Seeking Strategic Response to Future Society Changes," Korea Institute of S&T Evaluation and Planning, KISTEP R&D InI, Vol.15, pp.45-58, 2016.
  11. Taebok Yoon and Jee-hyong Lee, "A Study on Learner Modeling Technology and Applications for Intelligent Tutoring Systems," Journal of the Korea Academia-Industrial Cooperation Society, Vol.14, No.12 pp.6455-6460, 2013. https://doi.org/10.5762/KAIS.2013.14.12.6455