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Throwing Money at Schools
Open accessAbstract
The conventional wisdom about public schools is that they face serious problems in terms of performance and that improving schools requires additional money. However, the available evidence suggests that there is no relationship between expenditures and the achievement of students and that such traditional remedies as reducing class sizes or hiring better trained teachers are unlikely to improve matters. Furthermore, there is little reason to believe that schools will move toward more efficient operations, either on their own or through consumer pressures. More attention should be given to developing direct performance incentives.
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Citations
Cited by
Effects of Teachers’ Mathematical Knowledge for Teaching on Student Achievement
Hill, H. C., Rowan, B., & Ball, D. L. (2005) · American Educational Research Journal · doi:10.3102/00028312042002371 · Cited by 2,812
(1986) · Journal of Economic Literature · Cited by 2,705
Popay, J., Roberts, H., Sowden, A., Petticrew, M., Arai, L., Rodgers, M., Britten, N., Roen, K., & Duffy, S. (2006) · Lancaster University · doi:10.13140/2.1.1018.4643 · Cited by 2,070
Assessing the Effects of School Resources on Student Performance: An Update
Hanushek, E. A. (1997) · Educational Evaluation and Policy Analysis · doi:10.3102/01623737019002141 · Cited by 1,612
Self-citationCeci, S. J. (1991) · Developmental Psychology · doi:10.1037/0012-1649.27.5.703 · Cited by 837
Metadata
- Authors
- Hanushek, E. A.
- Venue
- Journal of Policy Analysis and Management
- Publisher
- JSTOR
- Published
- 1981
- Volume
- 1
- Issue
- 1
- Pages
- 19
- ISSN
- 0276-8739 (ISSN-L)
- OpenAlex
- W1983335363
- Cited by
- 282
- References
- 0
- FWCI
- 41.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Data sources
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.
