This study was supported by an Alexander von Humboldt Foundation fellowship (to K. Murayama) and four grants from the German Research Foundation (DFG; to R. Pekrun, Project for the Analysis of Learning and Achievement in Mathematics, PALMA; PE 320/11-1, PE 320/11-2, PE 320/11-3, PE 320/11-4).
Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies
Article first published online: 20 DEC 2012
© 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.
Volume 84, Issue 4, pages 1475–1490, July/August 2013
How to Cite
Murayama, K., Pekrun, R., Lichtenfeld, S. and vom Hofe, R. (2013), Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies. Child Development, 84: 1475–1490. doi: 10.1111/cdev.12036
- Issue published online: 12 JUL 2013
- Article first published online: 20 DEC 2012
- Alexander von Humboldt Foundation
- German Research Foundation. Grant Numbers: PE 320/11-1, PE 320/11-2, PE 320/11-3, PE 320/11-4
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.