English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 55184/89457 (62%)
造访人次 : 10677103      在线人数 : 61
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/57429


    题名: Applying Hybrid Data Mining Techniques to Web-based Self-Assessment System of Study and Learning Strategies Inventory
    作者: Shih, Chien-Chou;Chiang, Ding-An;Lai, Sheng-Wei;Hu, Yen-Wei
    贡献者: 淡江大學資訊傳播學系;淡江大學資訊工程學系;淡江大學通識與核心課程中心
    关键词: Data mining;Association rule;Decision tree;Self-assessment;LASSI
    日期: 2009-04
    上传时间: 2011-09-14 14:40:49 (UTC+8)
    出版者: Kidlington: Pergamon
    摘要: Traditional assessment tools, such as “Learning and Study Strategy Scale Inventory (LASSI)”, are typically pen-and-paper tests that require responses to a multitude of questions. This may easily lead to student’s resistance, fatigue and unwillingness to complete the assessment. To improve the situation, a hybrid data mining technique was applied to analyze the LASSI surveys of freshmen students at Tamkang University. The most significant contribution of this research is in dynamically reducing the number of questions while the LASSI assessment is proceeding. To verify the appliance of the proposed method, a web-based LASSI self-assessment system (Web-LSA) was developed. This system can be used as a guide to determine study disturbances for high-risk groups, and can provide counselors with fundamental information on which to base follow-up counseling services to its users.
    關聯: Expert Systems with Applications 36(3)pt.1, pp.5523-5532
    DOI: 10.1016/j.eswa.2008.06.089
    显示于类别:[資訊傳播學系暨研究所] 期刊論文
    [資訊工程學系暨研究所] 期刊論文
    [通識與核心課程中心] 期刊論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    Applying Hybrid Data Mining Techniques to Web-based Self-Assessment System of Study and Learning Strategies Inventory.pdf910KbAdobe PDF0检视/开启
    index.html0KbHTML59检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈