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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/118638


    Title: Improving Effectiveness of Learners’ Review of Video Lectures by Using an Attention-based Video Lecture Review Mechanism based on Brainwave Signals
    Authors: 林永騰
    Lin, Yong-Teng
    陳志銘
    Chen, Chih-Ming
    Contributors: 圖檔所
    Keywords: Attention awareness mechanism;sustained attention;brainwave;video lecture;review effectiveness
    Date: 2018
    Issue Date: 2018-07-12 17:38:49 (UTC+8)
    Abstract: Online video-based learning has been increasingly used in educational settings. However, students usually do not have enough cognitive capacity and metacognition skills to diagnose and record their attention status during learning tasks by themselves. This study thus presents an attention-based video lecture review mechanism (AVLRM) that can generate video segments for review based on students’ sustained attention status, as determined using brainwave signal detection technology. A quasi-experiment nonequivalent control group design was utilized to divide 55 participants from two classes of an elementary school in New Taipei City, Taiwan, into two groups. One class was randomly assigned to the experimental group, and used video lectures with the AVLRM support for learning. The other class was assigned to the control group, and used video lectures with autonomous review for learning. Analytical results indicate that students in the experimental group exhibited significantly better review effectiveness than did the control group, and this difference was especially marked for students who had a low attention level, were field-dependent, or were female. The findings show that AVLRM based on brainwave signal detection technology can precisely identify video segments that are more useful for effective review than those picked by student themselves. This study contributes to the design of learning tools that aim to support independent learning and effective review in online or video-based learning environments.
    Relation: Interactive Learning Environments, Published online: 20 Mar 2018
    7th International Congress on Advanced Applied Informatics | July 8-12 & 13, 2018 | Yonago, Tottori, Japan
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1080/10494820.2018.1451899
    DOI: 10.1080/10494820.2018.1451899
    Appears in Collections:[圖書資訊與檔案學研究所] 期刊論文

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