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Motivating Factors and Potential Deterrents of Using Wikipedia in Teaching in Higher Education

机译:使用维基百科在高等教育教学中使用维基百科的激励因素和潜在威慑

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Data mining techniques have been shown its success in analyzing data to assist factors and make decisions in many different applications. In this work, we analyzed universities' faculty members attitudes toward using Wikipedia in teaching in higher education. This may help in developing appropriate solutions to improve Wikipedia's effectiveness in education and provide the developers of Wikipedia with factors that may negatively impact using Wikipedia in teaching in higher education. Three different classification algorithms (Jrip Rule, Decision tree (J48) and Na?ve Bayes) have been carried out in the free and open source software WEKA (Waikato Environment for Knowledge Analysis) on used dataset. The accuracy and Receiver Operating Characteristic curves for all classifiers discussed. Our results show that there are some factors influences the faculty using of Wikipedia in activity teaching which are unobserved in other studies.
机译:数据挖掘技术已被证明其在分析数据时取得了成功,以促进因素,并在许多不同的应用中做出决策。在这项工作中,我们分析了大学的教师成员对高等教育教学中使用维基百科的态度。这可能有助于制定适当的解决方案,以提高维基百科在教育的有效性,并为维基百科的开发商提供可能对高等教育教学中的影响可能产生负面影响的因素。在使用的数据集上的自由和开源软件Weka(Waikato环境中)进行了三种不同的分类算法(JRIP规则,决策树(J48)和NA?VE贝叶斯)。讨论所有分类器的准确性和接收器操作特征曲线。我们的研究结果表明,有一些因素影响了维基百科在其他研究中的活动教学中使用维基百科的教师。

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