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Toward a Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning

机译:面向模糊域本体的自适应电子学习方法

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摘要

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.
机译:随着电子学习(e-Learning)技术在各级教育中的广泛应用,从相应的e-Learning环境中生成了越来越多的在线教育资源和消息。然而,对于教师而言,即使不是完全不可能,也很难通读并分析在线消息以预测学生的飞行进度。本文的主要贡献是说明了一种新的概念图生成机制,该机制以模糊域本体提取算法为基础。所提出的机制可以基于发布到在线讨论论坛的消息自动构建概念图。通过浏览概念图,讲师可以快速识别学生的学习进度并即时调整教学顺序。我们的初步实验结果表明,自动生成的概念图的准确性和质量很有希望。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,以增强电子学习。

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