Hattie maakt het concept van effectgrootte (effect size) zeer populair in onderwijs, maar wat is nu echt een groot effect? Robert Slavin beantwoordt deze vraag in een nieuwe blog post, en nee, het is niet “groter dan .40”.
So what’s the right answer? The answer turns out to mainly depend on just two factors: Sample size, and whether or not students, classes/teachers, or schools were randomly assigned (or assigned by matching) to treatment and control groups. We recently did a review of twelve published meta-analyses including only the 611 studies that met the stringent inclusion requirements of our Best-Evidence Encyclopedia (BEE). (In brief, the BEE requires well-matched or randomized control groups and measures not made up by the researchers.) The average effect sizes in the four cells formed by quasi-experimental/randomized and small/large sample size (splitting at n=250) are as follows.
Here is what this chart means. If you look at a study that meets BEE standards and students were matched before being (non-randomly) assigned to treatment and control groups, then the average effect size is +0.32. Studies that use the same sample sizes and design would need to reach an effect size like this to be at the average. In contrast, if you find a large randomized study, it will need an effect size of only +0.11 to be considered average for its type. If Program A reports an effect size of +0.20 and Program B reports the same, are the programs equally effective? Not if they used different designs. If Program A used a large randomized study design and Program B a small quasi-experiment, then Program A is a leader in its class and Program B is a laggard.
This chart only applies to studies that meet our BEE standards, which removes a lot of the awful research that gives Hattie the false impression that everything works, and fabulously.