采用基于教育信息学的学生数据比较分析,引入新的IR标准

Kunihiko Takamatsu, Katsuhiko Murakami, Yasuhiro Kozaki, Aoi Kishida, Takafumi Kirimura, Kenya Bannaka, Kenichiro Mitsunari, Masato Omori, Yasuo Nakata
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引用次数: 1

摘要

最近,我们提出了“教育信息学”,这是一个结合了教育和信息学的教育新领域。此外,我们引入了在机构研究(IR)中利用学生数据的新标准。在之前的一篇文章中,我们将“一手数据”定义为第一标准,它不是线性数据的组合;将“二级数据”定义为第二标准,它是一手数据的线性组合。然而,在本文中,我们将提出初级和次级数据的新定义,因为我们对实际教育数据的分析表明,次级数据不仅是线性数据,而且是非线性的。此外,我们将提供一些例子,其中主要数据用于检测无法通过分析次要数据建立的元素,并且是IR从业者进行比较分析的陷阱。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Introducing new criteria for IR, using student data compared analysis based on Eduinformatics
Recently, we proposed "Eduinformatics," a new field of education that combines both education and informatics. In addition, we introduced new criteria to utilize student data in Institutional Research (IR). In a previous article, we defined "primary data" as the first standard which is not combined linear data and "secondary data" as the second standard which is a linear combination of primary data. However, in this article we will present new definitions of Primary and Secondary data because our analysis of actual educational data has revealed that Secondary data is not only linear data, but also nonlinear. Moreover, we will present examples in which primary data was used to detect elements that could not be founded through the analysis of secondary data, and were pitfalls of compared analysis performed by IR practitioners.
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