COMMENT FAIRE DE LA PSEUDOSCIENCE AVEC DES DONNÉES RÉELLES : UNE CRITIQUE DES ARGUMENTS STATISTIQUES DE JOHN HATTIE DANS VISIBLE LEARNING PAR UN STATISTICIEN/HOW TO ENGAGE IN PSEUDOSCIENCE WITH REAL DATA: A CRITICISM OF JOHN HATTIE'S ARGUMENTS IN VISIBLE LEARNING FROM THE PERSPECTIVE OF A STATISTICIAN

This paper presents a critical analysis, from the point of view of a statistician, of the methodology used by Hattie in Visible Learning, and explains why it must absolutely be called pseudoscience. We first discuss what appears to be the intentions of Hattie's approach. Then we describe the ma...

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Bibliographic Details
Published in:McGill journal of education 2016-04, Vol.51 (2), p.935
Main Author: Bergeron, Pierre-Jérôme
Format: Article
Language:fre
Subjects:
Effect Size
Meta Analysis
Science
Online Access:Get full text
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Summary:This paper presents a critical analysis, from the point of view of a statistician, of the methodology used by Hattie in Visible Learning, and explains why it must absolutely be called pseudoscience. We first discuss what appears to be the intentions of Hattie's approach. Then we describe the major mistakes in Visible Learning before reviewing the set of questions a researcher should ask when investigating studies and surveys based on data analyses, including meta-analyses. We give concrete examples explaining why Cohen's d (the measure of effect size used in Visible Learning) simply cannot be used as some sort of universal measure of impact. Finally, we propose solutions to better understand and implement studies and meta-analyses in education.
ISSN:1916-0666