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Early Predictors of High School Mathematics Achievement
Open accessAbstract
Identifying the types of mathematics content knowledge that are most predictive of students’ long-term learning is essential for improving both theories of mathematical development and mathematics education. To identify these types of knowledge, we examined long-term predictors of high school students’ knowledge of algebra and overall mathematics achievement. Analyses of large, nationally representative, longitudinal data sets from the United States and the United Kingdom revealed that elementary school students’ knowledge of fractions and of division uniquely predicts those students’ knowledge of algebra and overall mathematics achievement in high school, 5 or 6 years later, even after statistically controlling for other types of mathematical knowledge, general intellectual ability, working memory, and family income and education. Implications of these findings for understanding and improving mathematics learning are discussed.
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Cited by
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Kiili, K., Moeller, K., & Ninaus, M. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.01.012 · Cited by 119
Lee, K., Ng, S. F., & Bull, R. (2018) · Developmental Psychology · doi:10.1037/dev0000561 · Cited by 33
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Metadata
- Authors
- Siegler, R. S., Duncan, G. J., Davis-Kean, P. E., Duckworth, K., Claessens, A., Engel, M., Susperreguy, M. I., & Chen, M.
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2012-06-14
- Volume
- 23
- Issue
- 7
- Pages
- 691-697
- ISSN
- 0956-7976 (ISSN-L)
- 1467-9280
- OpenAlex
- W2146066714
- Cited by
- 790
- References
- 0
- FWCI
- 35.06
- Type
- journal article
- Language
- en
- Open access
- green
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- Siegler, R. S., Duncan, G. J., Davis-Kean, P. E., Duckworth, K., Claessens, A., Engel, M., Susperreguy, M. I., & Chen, M. (2012). Early Predictors of High School Mathematics Achievement. Psychological Science. https://doi.org/10.1177/0956797612440101
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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