A Mixture Rasch Model Analysis of Mathematics Achievement

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.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.