Why is monitoring accuracy so poor in number line estimation? The importance of valid cues and systematic variability for U.S. college students
Author:
Funder
Institute of Education Sciences
Publisher
Springer Science and Business Media LLC
Subject
Education
Link
https://link.springer.com/content/pdf/10.1007/s11409-023-09345-y.pdf
Reference79 articles.
1. Alibali, M. W., & Sidney, P. G. (2015). Variability in the natural number bias: Who, when, how, and why. Learning and Instruction, 37, 56–61. https://doi.org/10.1016/j.learninstruc.2015.01.003
2. Baars, M., Wijnia, L., de Bruin, A., & Paas, F. (2020). The relation between students’ effort and monitoring judgments during learning: A meta-analysis. Educational Psychology Review, 32, 979–1002.
3. Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01
4. Booth, J. L., & Siegler, R. S. (2006). Developmental and individual differences in pure numerical estimation. Developmental Psychology, 42(1), 189. https://doi.org/10.1037/0012-1649.41.6.189
5. Booth, J. L., & Siegler, R. S. (2008). Numerical magnitude representations influence arithmetic learning. Child Development, 79(4), 1016–1031. https://doi.org/10.1111/j.1467-8624.2008.01173.x
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