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tandfonline.com – Using Multilevel Mixture Models in Educational Research: An Illustration with Homework Research

tandfonline.com har udgivet en rapport under søgningen “Teacher Education Mathematics”: Abstract Formulae display:?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom. Abstract The present study illustrates the utility of applying multilevel mixture models in educational research, using data on the homework behavior of 1,812 Swiss eighth-grade students in French as a second language. A previous person-centered study identified 5 homework learning types characterized by different patterns of high or low homework time and effort. Via multilevel latent profile analyses (MLPAs), the dependence of homework learning types on between-classroom differences was investigated. Based on the proportions of homework learning profiles across… Continue Reading

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Eric.ed.gov – Detecting Math Anxiety with a Mixture Partial Credit Model

eric.ed.gov har udgivet: The purpose of this study was to investigate a new methodology for detection of differences in middle grades students’ math anxiety. A mixture partial credit model analysis revealed two distinct latent classes based on homogeneities in response patterns within each latent class. Students in Class 1 had less anxiety about apprehension of math lessons and use of mathematics in daily life, and more self-efficacy for mathematics than students in Class 2. Moreover, students in Class 1 were found to be more successful in mathematics, mostly like mathematics and mathematics teachers, and have better educated mothers in comparison to students in Class 2. However, gender, attending private or public schools, and education levels of fathers did not appear to differ between the classes. Capturing such fine-grained information extends… Continue Reading