How to Engage in Pseudoscience With Real Data: A Criticism of John Hattie's Arguments in Visible Learning from the Perspective of a Statistician

Pierre-Jérôme Bergeron, McGill Journal of Education, Aug 20, 2017
Commentary by Stephen Downes
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This post is everything a proper refutation of education pseudoscience should be.It is a mistake to use Hattie's analysis as the basis for educational policy or instructional design, as this paper makes clear. Some context: in 2008 John Hattie published Visible Learning, which is essentially a meta-analysis of some 800 studies related to student achievement. The result was the Hattie Ranking of effect sizes. The work has been subject to numerous criticisms over the years, including this post noting "the Common Language Effect (CLE) is meant to be a probability, yet Hattie has it at values between -49% and 219%" , yet Hattie has continued to maintain his work is valid. He shouldn't. As this current post makes clear, the underlying presumption of the book is misguided. "Basically, Hattie computes averages that do not make any sense. A classic example of this type of average is: if my head is in the oven and my feet are in the freezer, on average, I’m comfortably warm."

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