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The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.

Using Kindergarten Number Sense to Predict Calculation Fluency in Second Grade

Open access
Locuniak, Maria N., Jordan, Nancy C.·2008·Journal of Learning Disabilities

Abstract

Children's number sense in kindergarten was used to predict their calculation fluency in second grade ( N = 198). Using block entry regression, usual predictors of age, reading, memory, and verbal and spatial cognition were entered in the first block and number sense measures were added in the second block. Number sense measures contributed a significant amount of variance over and above the more general predictors (26%—42%). Uniquely predictive subareas were active memory for numbers, number knowledge, and number combinations, with number combinations standing out as the strongest single predictor. Number sense screening in kindergarten, using “at-risk” versus “not-at-risk” criteria, successfully ruled out 84% of the children who did not go on to have calculation fluency difficulties and positively identified 52% of the children who later showed fluency difficulties. The relation of early number skills to later calculation fluency has important implications for math screening and intervention.

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Metadata

Authors
Locuniak, M. N., & Jordan, N. C.
Venue
Journal of Learning Disabilities
Published
2008-09
Volume
41
Issue
5
Pages
451-459
ISSN
  • 0022-2194 (ISSN-L)
  • 1538-4780
OpenAlex
W2086209126
Cited by
300
References
46
FWCI
12.73
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Using Kindergarten Number Sense to Predict Calculation Fluency in Second Grade. https://app.cochat.ai/papers/10.1177/0022219408321126
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Locuniak, M. N., & Jordan, N. C. (2008). Using Kindergarten Number Sense to Predict Calculation Fluency in Second Grade. Journal of Learning Disabilities. https://doi.org/10.1177/0022219408321126

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.