No Child Left Behind and Science Education: Opportunities, Challenges, and Risks
Abstract
This article examines the opportunities, challenges, and risks that No Child Left Behind (NCLB) poses for science education in elementary and middle schools. Four areas of science education—standards, instruction, teachers, and curriculum—are discussed in the present context of NCLB accountability. Attention is given to how the current policy agenda affects science education and how this agenda may influence the teaching and learning of science for years to come.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 44 · Cited by 194
- Authors
- Marx, R. W., & Harris, C. J.
- Affiliations
- University of Arizona (US)
- Venue
- The Elementary School Journal
- Publisher
- University of Chicago Press
- Published
- 2006-05
- Volume
- 106
- Issue
- 5
- Pages
- 467-478
- ISSN
- 0013-5984 (ISSN-L)
- 1554-8279
- OpenAlex
- W2161575566
- Cited by
- 194
- References
- 44
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 4 · 2023: 5 · 2022: 2 · 2021: 6 · 2020: 8 · 2019: 11 · 2018: 10 · 2017: 10 · 2016: 14 · 2015: 13 · 2014: 17 · 2013: 18 · 2012: 16
- FWCI
- 32.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Elementary School Journal (publishedVersion)
- Topics
- Social Sciences › Education › Science Education and Pedagogy
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Social Sciences › Education › School Choice and Performance
- Keywords
- No Child Left Behind Act, science education, educational accountability, elementary school, junior high school, science education standards, science instruction, science teachers, science curriculum, education policy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review