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Cited by 983

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Resources, Instruction, and Research

Cohen, David K., Raudenbush, Stephen W., Ball, Deborah Loewenberg·2003·Educational Evaluation and Policy Analysis

Abstract

Many researchers who study the relations between school resources and student achievement have worked from a causal model, which typically is implicit. In this model, some resource or set of resources is the causal variable and student achievement is the outcome. In a few recent, more nuanced versions, resource effects depend on intervening influences on their use. We argue for a model in which the key causal agents are situated in instruction; achievement is their outcome. Conventional resources can enable or constrain the causal agents in instruction, thus moderating their impact on student achievement. Because these causal agents interact in ways that are unlikely to be sorted out by multivariate analysis of naturalistic data, experimental trials of distinctive instructional systems are more likely to offer solid evidence on instructional effects.

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Metadata

Authors
Cohen, D. K., Raudenbush, S. W., & Ball, D. L.
Venue
Educational Evaluation and Policy Analysis
Published
2003-06
Volume
25
Issue
2
Pages
119-142
ISSN
  • 0162-3737 (ISSN-L)
  • 1935-1062
OpenAlex
W2109700222
Cited by
983
References
8
FWCI
108.28
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Resources, Instruction, and Research. https://app.cochat.ai/papers/10.3102/01623737025002119
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Cohen, D. K., Raudenbush, S. W., & Ball, D. L. (2003). Resources, Instruction, and Research. Educational Evaluation and Policy Analysis. https://doi.org/10.3102/01623737025002119

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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.