Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

Autor/inn/en	Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf
Titel	Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies
Quelle	In: Child Development, 84 (2013) 4, S.1475-1490 (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0009-3920
DOI	10.1111/cdev.12036
Schlagwörter	Mathematics Achievement; Achievement Gains; Cognitive Processes; Learning Strategies; Longitudinal Studies; Intelligence Quotient; Student Motivation; Predictor Variables; Correlation; Rewards; Foreign Countries; Secondary School Students; Socioeconomic Status; Age Differences; Gender Differences; Locus of Control; Track System (Education); Structural Equation Models; Germany; Cognitive Abilities Test + Suchen Sie Ihr Suchwort? Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Achievement gain; Leistungssteigerung; Cognitive process; Kognitiver Prozess; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Intelligenzquotient; Schulische Motivation; Prädiktor; Korrelation; Reward; Belohnung; Ausland; Sekundarschüler; Socio-economic status; Sozioökonomischer Status; Age; Difference; Age difference; Altersunterschied; Geschlechterkonflikt; Leistungsgruppe; Leistungsdifferenzierung; Deutschland
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; "M[subscript age]" = 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. (Contains 3 figures and 4 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10