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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/59989

    Title: Validating proficiency-mining strategy in adaptive learning environment
    Authors: Chen, Peng Wen;Shyu, Yuh Huei
    Contributors: 淡江大學資訊工程學系
    Keywords: programming proficiency;proficiency indicator;proficiency mining;adaptivity;learner-centred;distance learning;interactive learning environment;adaptive learning;web-based learning;internet;adaptive navigation;e-learning
    Date: 2004-05
    Issue Date: 2013-06-07 10:46:25 (UTC+8)
    Publisher: Geneva: Inderscience Publishers
    Abstract: The strategies of detecting learning state and generating relative adaptation link affect the success of adaptive navigation. Proficiency is a classic indicator in testing the learning state of programming. Similar to data mining, proficiency mining is added in the learning process to explore each learner's proficiency from observable behaviour. This paper presents a web-based learning system (NMPTE) embedded with a proficiency-mining strategy that is used for supporting adaptive navigation. The strategy involves using selected parameters to characterise the process of coding rehearsal. The criteria of selecting parameters are based on the psychology researches and the basic properties of learning to program. Web technologies with the standard of XML are adopted to describe adaptive curricula and proficiency parameters. Our experience demonstrates that proficiency mining shows sufficient evidence to represent programming performance and becomes a tool to detect users' features in adaptation system.
    Relation: International Journal of Continuing Engineering Education and Life-Long Learning 14(4-5), pp.370-387
    DOI: 10.1504/IJCEELL.2004.005727
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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