title: Predicting long-term growth in students' mathematics achievement: the unique contributions of motivation and cognitive strategies.
abstract: This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage  = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies.
authors.affiliation: Department of Psychology, University of Munich, Munich, Germany 80802. murakou@orion.ocn.ne.jp
authors.forename: Kou
authors.initials: K
authors.lastname: Murayama
authors.forename: Reinhard
authors.initials: R
authors.lastname: Pekrun
authors.forename: Stephanie
authors.initials: S
authors.lastname: Lichtenfeld
authors.forename: Rudolf
authors.initials: R
authors.lastname: Vom Hofe
mesh_terms: D000124:Achievement; D002648:Child; D003071:Cognition / Q000502:physiology*; D004522:Educational Status; D005260:Female; D006801:Humans; D007858:Learning / Q000502:physiology; D008137:Longitudinal Studies; D008297:Male; D008433:Mathematics; D009042:Motivation / Q000502:physiology*