Evaluation method and decision support of network education based on association rules

Junyan Zhao, Aixiang Wang
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Abstract

With the development of network technology, decision support and data mining has been widely applied in many fields, such as finance, marketing, quality analysis. But it isn't applied widely in the evaluation of network education. In order to improve the quality of personal training, universities regard the “the quality of teaching and teaching reform project” as the starting point, carry out teaching and management reform and explore the new talent cultivation mode. This paper summarizes the relative theories and methods of decision support, then introduces association rule in data mining. First, we analyze the classical association rules mining Apriori algorithm, then analyse this algorithm's disadvantages and improvement ways. Second, we use the Apriori algorithm, which can evaluate the network education from different aspects, thus providing manager with clear and actionable feedback to enhance their practice. Finally, the algorithm's efficiency is assessed and we points out the further research problems.
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基于关联规则的网络教育评价方法及决策支持
随着网络技术的发展,决策支持和数据挖掘在金融、市场营销、质量分析等领域得到了广泛的应用。但在网络教育评价中应用并不广泛。高校为提高人才培养质量,以“教学质量与教学改革工程”为抓手,开展教学与管理改革,探索人才培养新模式。总结了决策支持的相关理论和方法,介绍了数据挖掘中的关联规则。首先分析了经典关联规则挖掘Apriori算法,然后分析了该算法的缺点和改进方法。其次,我们使用了Apriori算法,该算法可以从不同的方面对网络教育进行评估,从而为管理者提供清晰可操作的反馈,以增强他们的实践能力。最后,对算法的有效性进行了评价,并指出了有待进一步研究的问题。
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