실천공학교육논문지 (Journal of Practical Engineering Education)

  • 제16권2호
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  • Pages.159-165
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  • 2024
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  • 2288-405X(pISSN)
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  • 2288-4068(eISSN)
한국실천공학교육학회 (Korean Institute for Pratical Engineering Education)
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학습자 중심의 맞춤형 교육을 위한 학습 경험 데이터 수집 및 분석 체계 연구

A Study on the Data Collection and Analysis System for Learning Experiences in Learner-Centered Customized Education

  • 김상우 (계명대학교 컴퓨터공학과) ;
  • 이명숙 (계명대학교 타불라라사칼리지)
  • Sang-woo Kim (Department of Computer Engineering, Keimyung University) ;
  • Myung-suk Lee (TabulaRasa Collage, Keimyung University)
  • 투고 : 2024.03.04
  • 심사 : 2024.03.23
  • 발행 : 2024.04.30
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초록

본 연구는 학습자 중심의 맞춤형 교육을 위한 지능형 학습활동 데이터를 수집하기 위한 전체 체계를 연구하였다. 학습활동 데이터수집 표준인 xAPI, Caliper analytics, cmi5의 특징들을 비교 분석하였고, 이러한 표준화된 데이터뿐만 아니라 표준화되지 않은 학습활동 데이터도 모두 빅데이터로 저장되어 인공지능 학습분석을 할 수 있는 체계를 마련하였다. 그 결과 데이터 유형 정의, xAPI 적용한 학습데이터 표준화, 빅데이터 저장, 학습분석(통계 기반 및 AI 기반), 학습자 맞춤형 서비스인 5개의 단계로 구성하였다. 이를 통해 인공지능 기술을 적용한 학습데이터 분석을 위한 기반을 마련하고자 하였다. 향후 연구에서는 전체 체계를 3개의 단계로 나누어 구현하고 실행하면서 설계에서 부족한 부분을 수정·보완할 것이다.

This study investigates the comprehensive system for collecting intelligent learning activity data tailored to learner-centered personalized education. We compared and analyzed the characteristics of xAPI, Caliper analytics, and cmi5, which are learning activity data collection standards, and established a system that allows not only standardized data but also non-standardized learning activity data to be stored as big data for artificial intelligence learning analysis. As a result, the system was structured into five stages: defining data types, standardizing learning data using xAPI, storing big data, conducting learning analysis (statistical and AI-based), and providing learner-tailored services. The aim was to establish a foundation for analyzing learning data using artificial intelligence technology. In future research, we will divide the entire system into three stages, implement and execute it, and correct and supplement any shortcomings in the design.

키워드

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