인공지능 기반 학습 지원 시스템에 관한 사례 분석

• 영문명: Case Analysis on AI-Based Learning Assistance Systems
• 발행기관: 한국공학교육학회
• 저자명: 지현경(Hyunkyung Chee) 김민지(Minji Kim) 이가영(Gayoung Lee) 허선영(Sunyoung Huh) 김명선(Myung sun Kim)
• 간행물 정보: 『공학교육연구』제27권 제4호, 3~11쪽, 전체 9쪽
• 주제분류: 공학 > 기타공학
• 파일형태: PDF
• 발행일자: 2024.07.31

국문 초록

This study classified domestic and international systems by type, presenting their key features and examples, with the aim of outlining future directions for system development and research. AI-based learning assistance systems can be categorized into instructional-learning evaluation types and academic recommendation types, depending on their purpose. Instructional-learning evaluation types measure learners' levels through initial diagnostic assessments, provide customized learning, and offer adaptive feedback visualized based on learners' misconceptions identified through learning data. Academic recommendation types provide personalized academic pathways and a variety of information and functions to assist with overall school life, based on the big data held by schools. Based on these characteristics, future system development should clearly define the development purpose from the planning stage, considering data ethics and stability, and should not only approach from a technological perspective but also sufficiently reflect educational contexts.

목차

Ⅰ. 서 론

Ⅱ. 이론적 배경

Ⅲ. 연구 방법

Ⅳ. 사례 분석 결과 및 시사점

Ⅴ. 결론 및 논의

참고문헌

키워드

Artificial intelligence AI-based learning assistance system Instructional-learning evaluation system Academic recommendation system Case analysis