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Questions as data: illuminating the potential of learning analytics through questioning an emergent field

机译:作为数据的问题:通过质疑紧急领域来阐明学习分析的潜力

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Abstract In providing a meta-analysis of a series of workshop papers and questions arising on the emergent field of learning analytics, this paper contributes to the ongoing formation of a shared research agenda. The first ICCE Learning Analytics workshop in 2014 demonstrated the effectiveness of a focused questioning session for collecting relevant data beyond the content of the papers themselves. In December 2014, approximately 40 participants attended the workshop held in Nara, Japan, and contributed to the collection of open research questions. Six papers were presented covering topics including scope; interoperability standards; privacy and control of individual data, extracting data from learning content and processes; and the development of conceptual frameworks. These papers established a base from which the group generated a set of questions that invite further investigation. Utilising the first stage of the Question Formulation Technique, a pedagogical approach designed to stimulate student inquiry, a prominent finding from the workshop that questions emerging from focused inquiry provide a useful set of data in their own right. With an explicit workshop focus on learning analytics interoperability, this paper reports on the emergent issues identified in the workshop and the kinds of questions associated with each issue in the context of current research in the field of learning analytics. The study considers the complexity arising from the fact that data associated with learning is itself becoming a digital learning resource while also enabling analysis of learner behaviours and systems usage.
机译:摘要在对一系列研究论文和在学习分析的新兴领域中出现的问题进行荟萃分析时,本文为正在进行的共享研究议程的形成做出了贡献。 2014年举行的首届ICCE学习分析研讨会证明了有针对性的质询环节可以有效收集论文本身之外的相关数据。 2014年12月,约40名参与者参加了在日本奈良举行的研讨会,并为收集公开研究问题做出了贡献。提出了六篇论文,涉及的主题包括范围;互操作性标准;隐私和个人数据控制,从学习内容和过程中提取数据;以及概念框架的发展。这些论文奠定了基础,该小组从中提出了一系列问题,需要进一步调查。利用问题制定技术的第一阶段,一种旨在激发学生探究性的教学方法,这是研讨会的一项重要发现,即集中探究产生的问题本身就提供了有用的数据集。在专门针对学习分析互操作性的研讨会上,本文报告了研讨会中发现的紧急问题以及在学习分析领域当前研究的背景下与每个问题相关的问题的种类。这项研究认为,与学习相关的数据本身已成为一种数字学习资源,同时还能够分析学习者的行为和系统使用情况,从而产生了复杂性。

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