Meta‐Analysis of <scp>PISA</scp> Creative Thinking Assessment Data: A Guide for Creativity Researchers

ABSTRACT Interest in understanding creativity through Programme for International Student Assessment (PISA) data is on the rise, yet researchers face methodological challenges in synthesizing findings across various constructs, measures, and datasets. Meta‐analysis—a valuable methodology for synthesizing quantitative data—remains underutilized in creativity research involving large‐scale assessments like PISA. This paper provides guidelines for applying meta‐analytic techniques to PISA creative thinking assessment data to help researchers address these challenges. It introduces meta‐analysis by outlining its definition and advantages, followed by key steps and methodological considerations for synthesizing bivariate and multivariate relationships within PISA. Finally, the paper discusses techniques for managing the computational complexity of meta‐analyzing PISA data. Ultimately, these guidelines aim to support researchers in effectively synthesizing PISA data to advance the study of creativity.

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Publication Details

Journal
The Journal of Creative Behavior
Published
2025-06-20
DOI
https://doi.org/10.1002/jocb.70046
Citations
1
Primary Topic
Creativity in Education and Neuroscience
Type
article
Field-Weighted Citation Impact
2.12
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article

Meta‐Analysis of PISA Creative Thinking Assessment Data: A Guide for Creativity Researchers

Sameh Said‐Metwaly, Wim Van Den Noortgate, Belén Fernández‐Castilla
1 citations
The Journal of Creative Behavior
Creativity in Education and Neuroscience
2.12
article

Meta‐Analysis of PISA Creative Thinking Assessment Data: A Guide for Creativity Researchers

Sameh Said‐Metwaly, Wim Van Den Noortgate, Belén Fernández‐Castilla
article en
1 citations

Abstract

ABSTRACT Interest in understanding creativity through Programme for International Student Assessment (PISA) data is on the rise, yet researchers face methodological challenges in synthesizing findings across various constructs, measures, and datasets. Meta‐analysis—a valuable methodology for synthesizing quantitative data—remains underutilized in creativity research involving large‐scale assessments like PISA. This paper provides guidelines for applying meta‐analytic techniques to PISA creative thinking assessment data to help researchers address these challenges. It introduces meta‐analysis by outlining its definition and advantages, followed by key steps and methodological considerations for synthesizing bivariate and multivariate relationships within PISA. Finally, the paper discusses techniques for managing the computational complexity of meta‐analyzing PISA data. Ultimately, these guidelines aim to support researchers in effectively synthesizing PISA data to advance the study of creativity.

The Journal of Creative BehaviorVol. 59(3)
Damanhour University (EG), Universidad Nacional de Educación a Distancia (ES), IMEC (BE), KU Leuven (BE)
Openalex Percentile: Top 13%
Creativity in Education and Neuroscience
2.12
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