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首页> 外文期刊>International journal of technology policy and management >A pedagogic method helps to create an actionable policy from big data through a PDCA cycle
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A pedagogic method helps to create an actionable policy from big data through a PDCA cycle

机译:教学方法有助于通过PDCA周期从大数据中创建可行的策略

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摘要

Big data and learning analytics for higher education is a rapidly growing field with disruptive potential. However, there has been little research reported on a pedagogic method that helps to create an actionable policy from big data. In recent years, there is a meaningful debate that big data alone cannot improve teaching, and more research is needed from a pedagogic point of view. We, therefore, developed a pedagogic method called BDAL (big data for active learning) that helps to create an actionable policy through a PDCA (plan-do-check-act) cycle. It facilitates students to examine their goals and motivations, to improve learning styles, and to be an active learner. An experiment was conducted on 556 undergraduate students for a control group and an experimental group. With the help of BDAL, we were able to gain an actionable policy to improve education further both in and out of classrooms.
机译:高等教育的大数据和学习分析是一个快速发展的领域,具有破坏性潜力。但是,关于用于从大数据创建可行策略的教学方法的研究报道很少。近年来,有一个有意义的辩论,即仅大数据并不能改善教学,并且从教育学的角度来看,还需要进行更多的研究。因此,我们开发了一种称为BDAL(用于主动学习的大数据)的教学方法,该方法有助于通过PDCA(计划-执行-检查-执行)周期制定可行的政策。它可以帮助学生检查自己的目标和动机,改善学习方式,并成为积极的学习者。在556名大学生中进行了实验,分别是对照组和实验组。在BDAL的帮助下,我们获得了可行的政策,以进一步改善课堂内外的教育。

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