The Big-Fish-Little-Pond Effect for Reading Self-Beliefs: A Cross-National Exploration with PISA 2018

G. Basarkod*, H. Marsh, J. Guo, T. Dicke, M. Xu, P. Parker

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Past research shows the Big-Fish-Little-Pond Effect (BFLPE; negative effect of school-average achievement on student-level academic self-concept) to generalize across countries. However, such evidence is largely limited to math and science. Given that reading self-concept is highly differentiated from math and science self-concepts and plays an important role in predicting educational outcomes, it is essential to examine the universality of the BFLPE and its underlying social-comparison process within this domain.
We assess the cross-national generalizability of the BFLPE for 15-year-olds’ reading self-concept using Programme for International Students Assessment 2018 (533,165 students, 72 countries). To demonstrate that the BFLPE operates with a relative—rather than absolute—frame of reference for comparison, we juxtapose difficulty experienced with reading in general (self-concept perceived difficulty; relative frame of reference), with difficulty experienced with reading specifically during the PISA test (PISA test difficulty; absolute frame of reference).
Our findings show that the BFLPE for both the reading self-concept perceived competence and difficulty subscales was robust across countries. Further, the BFLPE was strong for self-concept subscales, but very weak for the PISA test difficulty scale.
Our findings extend support for the generalizability of the BFLPE to reading self-concept and highlight the role of social comparison processes underlying this effect.
Original languageEnglish
Pages (from-to)375-392
Number of pages18
JournalScientific Studies of Reading
Issue number4
Early online date5 Feb 2023
Publication statusPublished - 2023


Dive into the research topics of 'The Big-Fish-Little-Pond Effect for Reading Self-Beliefs: A Cross-National Exploration with PISA 2018'. Together they form a unique fingerprint.

Cite this