{"title":"A Mixture Rasch Model Analysis of Mathematics Achievement","authors":"Halime Yıldırım Hoş, Menekşe Uysal Saraç","doi":"10.24106/kefdergi.1246453","DOIUrl":null,"url":null,"abstract":"Purpose: This study aims to determine distinct latent classes in 8th-grade students' mathematics achievement \nDesign: 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. \nFindings: 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. \nHighlights: 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.","PeriodicalId":33167,"journal":{"name":"Kastamonu Egitim Dergisi","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Kastamonu Egitim Dergisi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24106/kefdergi.1246453","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.