English  |  正體中文  |  简体中文  |  Post-Print筆數 : 11 |  Items with full text/Total items : 88613/118155 (75%)
Visitors : 23470913      Online Users : 217
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/120340


    Title: Community Detection with Opinion Leaders’ Identification for Promoting Collaborative Problem-based Learning Performance
    Authors: 陳志銘
    Chen, Chih-Ming
    游宗霖
    You, Zong-Lin
    Contributors: 圖檔所
    Date: 2019-07
    Issue Date: 2018-10-02 17:30:16 (UTC+8)
    Abstract: In the 21st century when knowledge‐based economy is emphasized, the cultivation of autonomous learning and problem‐solving abilities presents the importance. With web‐based collaborative problem‐based learning (CPBL), learners could more conveniently cultivate their problem‐solving abilities through autonomous learning. Nevertheless, learners are often guided to solve a target problem by the information announced by teachers during the CPBL processes. Individual learners often could not effectively absorb such standard information, thus ignoring the important information from teachers. In the information communication theory, the two‐step flow of communication through opinion leaders has been proved that it can better change audiences’ attitudes than the one‐step flow of communication through mass media. This study thus employs the modularity Q function as the fitness function of genetic algorithm to optimally detect learning communities and uses PageRank measure to accurately find out community opinion leaders according to the social network interaction data of learners in the CPBL process. Based on quasi‐experimental design, this study examines whether learners in the experimental group using the two‐step flow of communication through opinion leaders to convey information for solving the target CPBL missions could more significantly enhance web‐based CPBL performance, social network interaction and group cohesion than learners in the control group using the one‐step flow of communication through teachers’ information. Analytical results show learners in the experimental group remarkably outperform those in the control group on learning performance and peer interaction under a CPBL environment. Particularly, female learners in the experimental group notably outperform female learners in the control group on learning performance, while there is no significant difference in male learners between both groups. More importantly, learners in the experimental group present significantly higher group cohesion than those in the control group. This study confirms that using the two‐step flow of communication instead of the one‐step flow of communication traditionally used in web‐based learning environments could significantly promote web‐based CPBL performance, social network interaction and group cohesion.
    Relation: British Journal of Educational Technology, 50(4), 1846-1864
    Data Type: article
    DOI 連結: https://doi.org/10.1111/bjet.12673
    DOI: 10.1111/bjet.12673
    Appears in Collections:[圖書資訊與檔案學研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    12673.pdf596KbAdobe PDF226View/Open
    Community Detection with Opinion Leaders’ Identification for Promoting Collaborative Problem-based Learning Performance _revised__post print_.pdfPost-Print version597KbAdobe PDF1View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback