A new approach for constructing the concept map
A new approach for constructing the concept map
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DOI：
10.1016/j.compedu.2005.11.020
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发表时间：
2004-08
期刊：
影响因子：
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通讯作者：
S. Tseng;P. Sue;Jun-Ming Su;Jui-Feng Weng;Wen-Nung Tsai
中科院分区：
文献类型：
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作者：
S. Tseng;P. Sue;Jun-Ming Su;Jui-Feng Weng;Wen-Nung Tsai
近年来，电子学习系统变得越来越流行，并且已经提出了许多自适应学习环境，以根据学习者的才能和学习结果为他们提供定制课程。为了实现自适应学习，通常使用预定义的课程概念图来为学习者提供自适应学习指导。然而，创建课程的概念图是困难且耗时的。因此，如何自动创建课程的概念图就成为一个有趣的问题。在本文中，我们提出了一种两阶段概念图构建（TP-CMC）方法，通过学习者的历史测试记录自动构建概念图。第一阶段用于预处理测试记录；即转换数字成绩数据，细化测试记录，并从输入数据中挖掘关联规则。第二阶段用于将挖掘的关联规则转化为学习概念之间的前提关系，以创建概念图。因此，在第一阶段，我们应用模糊集理论将学习者的数值测试记录转化为符号数据，应用教育理论进一步细化它，并应用数据挖掘方法找到其成绩模糊关联规则。然后，在第二阶段，根据我们对实际学习情况的观察，我们使用多种规则类型进一步分析挖掘的规则，然后提出一种启发式算法来自动构建概念图。最后，还讨论了构建的概念图的冗余性和循环性。此外，我们还开发了TP-CMC原型系统，然后利用初中学生的真实测试记录来评估结果。实验结果表明我们提出的方法是可行的。
In recent years, e-learning system has become more and more popular and many adaptive learning environments have been proposed to offer learners customized courses in accordance with their aptitudes and learning results. For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance for learners. However, it is difficult and time consuming to create the concept map of a course. Thus, how to automatically create a concept map of a course becomes an interesting issue. In this paper, we propose a Two-Phase Concept Map Construction (TP-CMC) approach to automatically construct the concept map by learners’ historical testing records. Phase 1 is used to preprocess the testing records; i.e., transform the numeric grade data, refine the testing records, and mine the association rules from input data. Phase 2 is used to transform the mined association rules into prerequisite relationships among learning concepts for creating the concept map. Therefore, in Phase 1, we apply Fuzzy Set Theory to transform the numeric testing records of learners into symbolic data, apply Education Theory to further refine it, and apply Data Mining approach to find its grade fuzzy association rules. Then, in Phase 2, based upon our observation in real learning situation, we use multiple rule types to further analyze the mined rules and then propose a heuristic algorithm to automatically construct the concept map. Finally, the Redundancy and Circularity of the concept map constructed are also discussed. Moreover, we also develop a prototype system of TP-CMC and then use the real testing records of students in junior high school to evaluate the results. The experimental results show that our proposed approach is workable.