Predicting children's developmental trajectories of math achievement from learning motivation profiles: a person-centered approach

This study utilized latent class growth modeling (LCGM) to identify four kinds of math achievement trajectories across grades 4-6. In addition latent profile analysis (LPA) was used to Identify four motivational profiles in grade 4. We also examined the relation between these math achievement trajectories and motivational profiles. Data were collected from 3,772 children. Results showed that only children in the "high quality" motivation profile had greater probabilities of following favorable math achievement developmental patterns. This result indicated that motivation quality is more important than the amount of motivation not only for children's current academic achievement but also for their academic developmental trajectories in the long term.