A Mixture Rasch Model Analysis of Mathematics Achievement

Halime Yıldırım Hoş, Menekşe Uysal Saraç
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Abstract

Purpose: This study aims to determine distinct latent classes in 8th-grade students' mathematics achievement Design: The research study group consisted of 435 students who received the first booklet at the TIMSS 2015 8th grade mathematics achievement test. A mixture of Rasch model analysis was used to find the best-fitting model. Findings: When model fit indices were evaluated, the model fitting the data was found to be MRM with the two latent classes. According to this model, students in latent class 2 are more successful in mathematics than students in latent class 1. The vast majority of the items are found easier in latent class 2. Highlights: In addition, the cognitive domain of the more accessible items for students in both classes is “knowing, while items that are difficult for both groups are in the “applying” cognitive domain.
数学成绩的混合Rasch模型分析
目的:本研究旨在确定八年级学生数学成就的不同潜在类别。设计:研究小组由435名在TIMSS 2015年八年级数学成就测试中收到第一本小册子的学生组成。采用混合Rasch模型分析来寻找最佳拟合模型。结果:当模型拟合指数进行评估时,发现与数据拟合的模型是两个潜在类别的MRM。根据这个模型,潜伏在2类的学生比潜伏在1类的学生在数学上更成功。绝大多数物品在潜在的2类中更容易被发现。亮点:另外,两组学生对较易理解的项目的认知域为“知道”,而对两组学生较难理解的项目则处于“应用”的认知域。
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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50 weeks
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