Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 517

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Meta-Analysis of Research on Class Size and Achievement

Glass, Gene V, Smith, Mary Lee·1979·Educational Evaluation and Policy Analysis

Abstract

THERE IS No POINT IN RECORDING THE obvious about class size: that teachers worry about it more than nearly anything else, that administrators want to increase it, that it is economically important, and the like. The problem with class size is the research. It is unclear. It has variously been read as supporting larger classes, supporting smaller classes, and supporting nothing but the need for better research. Review after review of the topic has dissolved into cynical despair or epistemological confusion. The notion is wide-spread among educators and researchers that class size bears no relationship to achievement. It is a dead issue in the minds of most instructional researchers. To return to the class-size literature in search of defensible interpretations and conclusions strikes many as fruitless. The endeavor is surrounded by a faint aroma of Chippendale, which it resembles in other respects: unwieldy and antique. One could document the confusion in previous reviews of research on the class-

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3102/01623737001001002

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 7 references

Cited by

See all 517

Metadata

Authors
Glass, G. V., & Smith, M. L.
Venue
Educational Evaluation and Policy Analysis
Published
1979-01
Volume
1
Issue
1
Pages
2-16
ISSN
  • 0162-3737 (ISSN-L)
  • 1935-1062
OpenAlex
W1969426771
Cited by
517
References
7
FWCI
15.06
Type
journal article
Language
en
Open access
closed

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Meta-Analysis of Research on Class Size and Achievement. https://app.cochat.ai/papers/10.3102/01623737001001002
The paper
Glass, G. V., & Smith, M. L. (1979). Meta-Analysis of Research on Class Size and Achievement. Educational Evaluation and Policy Analysis. https://doi.org/10.3102/01623737001001002

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.