Latent profile analysis reveals distinct mathematical modeling competencies across countries, suggesting implications for education.
We investigated the classification of learner groups for students' mathematical modeling competency and analyzed the characteristics in each profile group for each country and variable using PISA 2012 data from six countries.With a perspective on measuring subcompetency, we applied the latent profile analysis method to student achievement for mathematical modeling variables -Formulate, Employ, Interpret.The findings showed the presence of 4-6 profile groups, with the variables exhibiting high and low achievement within each profile group varying by country, and a hierarchical structure was observed in the profile group distribution in all countries, interestingly, the Formulate variable showed the largest difference between high-achieving and lowachieving profile groups.These results have significant implications.Comparison by country, variable, and profile group can provide valuable insights into understanding the various characteristics of students' mathematical modeling competency.The Formulate variable could serve as the most suitable predictor of a student's profile group and the score range of other variables.We suggest further studies to gain more detailed insights into mathematical modeling competency with different cultural contexts.
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Jeong et al. (2023) studied this question.
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