基于Rasch模型的另一种学习增益

H. Nitta, Takuya Aiba
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引用次数: 3

摘要

利用Rasch模型进行前测后测分析,引入学习增益,即“Rasch增益”,作为学生估计能力参数的简单差值。研究表明,尽管Rasch增益与Hake引入的归一化学习增益密切相关,但作为一种科学度量,Rasch增益比Hake增益具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Alternative Learning Gain Based on the Rasch Model
Using the Rasch model for the pretest–posttest analysis, a learning gain, the “Rasch gain”, is introduced as the simple difference of the estimated ability parameter for students. It is shown that, although the Rasch gain strongly correlates with the normalized learning gain introduced by Hake, the Rasch gain has advantages over the Hake gain as a scientific measure.
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