How have researchers of TESOL analyzed data? How can they do it better?

What is it about?

When I wrote this article practices of inferential statistics (e.g., null hypothesis significance testing) in research of instructed second language learning were on the whole remarkably outdated. A cause of this situation, I suspect, was training based around textbooks written by and for experimental psychologists working in fields that do not involve linguistic data. An indication of this is the fact that the survey I report in this article came across hardly any uses of mixed-effects modeling. So one of the things the article is about is better methods for the kinds of data analysis that L2 researchers typically engage in.

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Why is it important?

Because suboptimal statistical practices can result in misleading conclusions.

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