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    政大機構典藏 > 理學院 > 資訊科學系 > 會議論文 >  Item 140.119/120032
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/120032

    Title: Forecasting reading anxiety to promote reading performance based on annotation behavior
    Authors: Lu, T.-Y.;Lin, M.;Chen, Chen C.-M.;Wu, J.-H.
    Chen, Chihming
    Wu, Jhihhao
    Contributors: 圖檔所
    Keywords: C4.5 decision trees;Cooperative/collaborative learning;Experimental groups;Intelligent tutoring system;Interactive learning environment;Learning performance;Reading performance;Teaching/learning strategy;Computer aided instruction;Data mining;Decision trees;Forecasting;Learning systems
    Date: 2013
    Issue Date: 2018-09-06 17:41:04 (UTC+8)
    Abstract: To reduce effectively the reading anxiety of learners while reading English articles, a C4.5 decision tree, a widely used data mining technique, was used to develop a personalized reading anxiety prediction model (PRAPM) based on individual learners' reading annotation behavior in a collaborative digital reading annotation system. In addition to forecasting immediately the reading anxiety levels of learners, the proposed PRAPM can be used to identify the key factors that cause reading anxiety based on the fired prediction rules determined by the developed decision tree. By understanding these key factors that cause reading anxiety, instructors can apply reading strategies to reduce reading anxiety, thus promoting English-language reading performance. To assess whether the proposed PRAPM can assist instructors in reducing the reading anxiety of learners, this study applies the quasi-experimental method to compare the learning performance of three learning groups, which are supported by a collaborative digital reading annotation system with different learning mechanisms to reduce reading anxiety. The control group, experimental group A and experimental group B conducted the same English reading activity. However, each group was given a collaborative digital reading annotation system with individual annotations, cooperative annotations, and cooperative annotation with the instructor's support to reduce reading anxiety by proposed PRAPM. Experimental results indicate that the average correct prediction rate of the proposed PRAPM in identifying the reading anxiety levels of learners was as high as 70%. The online instructor who applied reading assistive strategies based on the mining factors that affect reading anxiety from the proposed PRAPM can significantly reduce the reading anxiety of male learners in the experimental group B, showing that gender difference existed, and the online instructor's interaction with the male learners of the experimental group B indeed helped reduce the reading anxiety. © 2013 IEEE.
    Relation: Proceedings - International Computer Software and Applications Conference, 2013, 論文編號 06605828, Pages 427-432
    2013 IEEE 37th Annual Computer Software and Applications Conference Workshops, COMPSACW 2013; Kyoto; Japan; 22 July 2013 到 26 July 2013; 類別編號E4987; 代碼 100165
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1109/COMPSACW.2013.132
    DOI: 10.1109/COMPSACW.2013.132
    Appears in Collections:[資訊科學系] 會議論文

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