4.5 Article

Ability Stratification Predicts the Size of the Big-Fish-Little-Pond Effect

Journal

EDUCATIONAL RESEARCHER
Volume 50, Issue 6, Pages 334-344

Publisher

SAGE PUBLICATIONS INC
DOI: 10.3102/0013189X20986176

Keywords

ability grouping; educational policy; hierarchical linear modeling; interdisciplinary approach; international comparison; meta-analysis; motivation; school psychology; self-concept; social stratification; structural equation modeling

Ask authors/readers for more resources

This study examines how country-level ability stratification is associated with the Big-Fish-Little-Pond Effects on math self-concept, using data from four cycles of international studies. The findings strongly support the hypothesis that more ability stratification leads to larger negative effects on academic self-concept. These results have important implications for school system design and policy-making.
Understanding how children's broader context influences their development is critical if we are to develop policies that help them flourish. Combining sociological, economic, and psychological literature, we argue that ability stratification-the degree to which children of similar levels of ability are schooled together-influences a child's academic self-concept. This is because countries with more ability stratification should have larger Big-Fish-Little-Pond Effects (the negative effect of school average achievement on academic self-concept). We used four cycles of the Trends in International Math and Science Study to test the hypothesis that more country-level ability stratification is associated with larger country-level Big-Fish-Little-Pond Effects for math self-concept. Findings strongly support this hypothesis. Our findings have implications for school system design and policy.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available