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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/37766


    Title: A cognition assessment authoring system for e-learning
    Authors: Hung, Jason C.;Lin, L. J.;Chang, Wen-chih;Shih, Timothy K.;Hsu, Hui-huang;Chang, Han-bin;Chang, Hsuan-pu;Huang, Kuan-hao
    Contributors: 淡江大學資訊工程學系
    Keywords: Cognition Level;Item Discrimination Index;Item Difficulty Index;Assessment Analysis Model;distance learning
    Date: 2004-03-23
    Issue Date: 2010-04-15 09:48:41 (UTC+8)
    Publisher: Institute of Electrical and Electronics Engineers(IEEE)
    Abstract: With the rapidly development of distance learning and the XML (Extensible Markup Language) technology, metadata becomes an important item in an e-learning system. Today, many distance learning standards such as SCORM, AICC CMI, IEEE LTSC learning object meta-data (LOM), and IMS learning resource metadata XML binding specification, use metadata to tag learning materials, shareable content objects, and learning resources. However, most metadata is used to define learning materials and test problems. Few metadata is dedicated for assessment in learning. We propose an assessment metadata model for e-learning operations. With the support from the assessment metadata, we can collect information at the question cognition level, item difficulty index, item discrimination index, questionnaire style, and question style. The assessment analysis model provides individual questions, summary of test results, and analytical suggestions. The suggestions and results can tell teachers why a question is not suitable and how to correct it. Teachers can see the analysis of test result and fix problematic questions. With the cognition level analysis, teachers can avoid missing items in teaching. The mechanism developed also suggests an e-learning system, with adaptive learning content and individualized tests, as well as good advice for the teachers.
    Relation: Distributed Computing Systems Workshops, 2004. Proceedings. 24th International Conference on, pp.262-267
    DOI: 10.1109/ICDCSW.2004.1284041
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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