Abstract

A person-centered approach was adopted to identify distinct classes of learning anxiety (LA) using 158,578 Grade 8 students in 1097 schools in China. Through a nonparametric multilevel latent class analysis, it identified a best-fitting model consisting of three student-level latent classes (low, moderate, and high LA) and three school-level latent classes (rare, moderate, and intense LA schools). To further examine the effects of potential covariates on the student and school latent classes of LA, a multinomial logistic regression was conducted. The main results were, first, girls exhibited a higher odds ratio in moderate and high student LA classes. What's more, students' total academic scores were positively related to their odds of being in the moderate LA class while negatively related to their odds of being in the high LA class. Lastly, school leadership, school belongingness, and teacher-student relationship were all negatively correlated with the odds that schools belong to the intense and moderate LA schools.

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