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计算机工程

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一种干部在线作弊学习行为分析与预测策略

陈乾国   

  1. (重庆工商大学 重庆干部教育研究中心,重庆 400067)
  • 收稿日期:2016-10-17 出版日期:2017-09-15 发布日期:2017-09-15
  • 作者简介:陈乾国(1984—),男,助理研究员、硕士,主研方向为复杂系统、大数据分析、教育信息化。
  • 基金资助:

    重庆市自然科学基金(cstc2013jcyjA40022);重庆市教委科学技术研究计划项目(KJ1706173)。

A Strategy for Analyzing and Predicting Online Cheating Learning Behavior of Cadres

CHEN Qianguo   

  1. (Education Research Center for Chongqing Carder,Chongqing Technology and Business University,Chongqing 400067,China)
  • Received:2016-10-17 Online:2017-09-15 Published:2017-09-15

摘要:

干部学习已通过互联网实现信息化与数字化,但部分干部采取作弊手段来完成学习要求。为提高干部学习质量与效益,针对利用插件等工具进行作弊学习的现象,根据防作弊规则,提出一种干部在线作弊学习的检测策略。通过分析学习数据发现作弊行为,并对作弊行为进行预测。应用结果表明,该策略能够有效提升在线学习质量,对学习效果做到准确评价,有利于促进干部在线教育的健康发展。

关键词: 在线学习, 学习记录数据集, 作弊行为检测, 作弊行为分析, 数据分析

Abstract:

The digitization and information of cadre learning mode is implemented through Internet,but some cadres learn by taking cheating means to complete the learning tasks.In order to improve the quality and effectiveness of the cadres online learning,for the phenomenon of cheating that uses tools such as plug-ins or learning assistants to learn,according to the anti-fraud rules of cadres online learning system,this paper proposes the corresponding fraud detection strategy.Through analyzing and data mining of the cadres learning records,trying to find their fraud behavior,at the same time,predicting other cadres’ fraud behavior.Application results show that the strategy can effectively enhance the cadres’ online learning quality and make accurate evaluation of the cadres’ learning effect,it is conductive to promoting the development of the cadre online education.

Key words: online learning, learning record dataset, cheating behavior detection, cheating behavior analysis, data analysis

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