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Abstract
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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 classrooms, 3 class-level profiles were identified: A “low time”, “high time” and an “average” profile. Predictors of the latent profiles at the student and class levels were assessed. The study offers insights into the advantages of multilevel mixture models for educational research.