온라인 학습을 위한 학생 피드백 분석 기반 콘텐츠 재구성 추천 프레임워크Restructure Recommendation Framework for Online Learning Content using Student Feedback Analysis
- Other Titles
- Restructure Recommendation Framework for Online Learning Content using Student Feedback Analysis
- Authors
- 최자령; 김수인; 임순범
- Issue Date
- Nov-2018
- Publisher
- 한국멀티미디어학회
- Keywords
- E-learning; Student Feedback; Content Restructuring; Learning Contents
- Citation
- 한국티미디어학회논문지, v.21, no.11, pp 1353 - 1361
- Pages
- 9
- Journal Title
- 한국티미디어학회논문지
- Volume
- 21
- Number
- 11
- Start Page
- 1353
- End Page
- 1361
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4163
- DOI
- 10.9717/kmms.2018.21.11.1353
- ISSN
- 1229-7771
2384-0102
- Abstract
- With the availability of real-time educational data collection and analysis techniques, the education paradigm is shifting from educator-centric to data-driven lectures. However, most offline and online education frameworks collect students’ feedback from question-answering data that can summarize their understanding but requires instructor’s attention when students need additional help during lectures. This paper proposes a content restructure recommendation framework based on collected student feedback. We list the types of student feedback and implement a web-based framework that collects both implicit and explicit feedback for content restructuring. With a case study of four-week lectures with 50 students, we analyze the pattern of student feedback and quantitatively validate the effect of the proposed content restructuring measured by the level of student engagement.
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