Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning
Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning
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DOI：
10.1109/tkde.2008.137
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发表时间：
2009-06
影响因子：
8.9
通讯作者：
Raymond Y. K. Lau;D. Song;Yuefeng Li;C. Cheung;Jin-Xing Hao
中科院分区：
文献类型：
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作者：
Raymond Y. K. Lau;D. Song;Yuefeng Li;C. Cheung;Jin-Xing Hao
随着电子学习（e-Learning）技术在各级教育中的广泛应用，相应的e-Learning环境产生了越来越多的在线教育资源和信息。然而，对于教师来说，通过阅读和分析在线信息来预测学生的进度是相当困难的，如果不是完全不可能的话。本文的主要贡献是阐述了一种新的概念图生成机制，该机制以模糊领域本体提取算法为基础。提出的机制可以根据发布到在线论坛的消息自动构建概念图。通过浏览概念图，教师可以快速确定学生的进度，并随时调整教学顺序。我们的初步实验结果表明，自动生成的概念图的精度和质量是有希望的。我们的研究工作为智能软件工具的开发和应用打开了大门，以加强电子学习。
With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.