New Proposal to Compare Student Data in Institutional Research

Yasuo Nakata, Katsuhiko Murakami, Yasuhiro Kozaki, Takafumi Kirimura, Aoi Sugiura, Kenya Bannaka, Kunihiko Takamatsu
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引用次数: 4

Abstract

This article proposes new criteria for using student data in universities. First criteria are called primary data and secondary criteria are called secondary data. We define primary data as those that are not linear combination data, and secondary data as a linear combination of primary data. For example, at the macro-level, primary data are correct and incorrect answers to a question in an examination or students' attendance and absence from a lecture. At the macro-level, secondary data are the total points in an examination or students' total attendance in and absence from a lecture. At the meso-level, secondary data are student records of lectures as well as grade point average, or rank, in the annual record of the university. Primary data are mainly constructed by faculty while secondary data are constructed by administrative staff. To compare primary and secondary data, collaboration between faculty and administrative staff is important.
比较院校研究中学生数据的新建议
本文提出了高校使用学生数据的新标准。第一标准称为主要数据,第二标准称为次要数据。我们将原始数据定义为非线性组合的数据,将辅助数据定义为原始数据的线性组合。例如,在宏观层面上,主要数据是考试中一个问题的正确答案和错误答案,或者学生出席和缺席讲座的情况。在宏观层面上,次要数据是考试的总分或学生上课和缺勤的总人数。在中观层面,二级数据是学生的讲课记录以及大学年度记录中的平均绩点或排名。一手数据主要由教师构建,二次数据主要由行政人员构建。为了比较一手数据和第二手数据,教师和行政人员之间的合作是很重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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