한국멀티미디어학회논문지 (Journal of Korea Multimedia Society)

  • 제21권11호
  • /
  • Pages.1353-1361
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  • 2018
  • /
  • 1229-7771(pISSN)
  • /
  • 2384-0102(eISSN)
한국멀티미디어학회 (Korea Multimedia Society)
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온라인 학습을 위한 학생 피드백 분석 기반 콘텐츠 재구성 추천 프레임워크

Restructure Recommendation Framework for Online Learning Content using Student Feedback Analysis

  • Choi, Ja-Ryoung (Research Institute of ICT Convergence, Sookmyung Women's University) ;
  • Kim, Suin (School of Computing, KAIST) ;
  • Lim, Soon-Bum (Dept. of Information Technology Engineering, Sookmyung Women's University)
  • 투고 : 2018.08.16
  • 심사 : 2018.10.22
  • 발행 : 2018.11.30
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초록

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.

키워드

MTMDCW_2018_v21n11_1353_f0001.png 이미지

Fig. 1. E-learning systems using student feedback.

MTMDCW_2018_v21n11_1353_f0002.png 이미지

Fig. 2. Overview of Recommendation Framework.

Table 1. Topics extracted from quiz-related questions

MTMDCW_2018_v21n11_1353_t0001.png 이미지

Table 2. Effect of proposed automatic updates

MTMDCW_2018_v21n11_1353_t0002.png 이미지

Table 3. Comparison chart of system

MTMDCW_2018_v21n11_1353_t0003.png 이미지

참고문헌

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