Does artificial intelligence help students learn? That’s a question many teachers and parents want answered, as the new educational technology is rapidly spreading in classrooms.
Normally, meta-analyses would be the right place to look, since they’re supposed to gather a scattered body of research and make sense of it by pointing to where the preponderance of evidence lies. And indeed, there are 39 of them, all reporting substantial benefits for AI in education.
But it appears that the studies synthesizing that evidence are themselves unreliable — and the peer-review process failed to catch the problems.
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Susanna Loeb, a Stanford professor of education who also joined the meta-analysis critique webinar, pointed out that her team has collected almost 900 studies on AI in education and determined that only 20 of them were of high enough quality to be included in a recent summary of the evidence for her AI Hub for Education. Her team has since identified 32 more studies and is soon to update that summary. But, she said, it’s still too early to conduct a meta-analysis that would be useful to school leaders or teachers. Very few of the high-quality studies take place in K-12 schools in the United States.
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