This is a short editorial introducing a special issue of Journal of Computing in Higher Education. Some of its recommendations are well worth noting. Data science extracts knowledge to address problems in education, they write, but "knowledge extracted is only applicable to the problem addressed." Moreover, "most research is focused on analyzing only one source of educational data." They "generate models that are hard to interpret". And the tools need to "adapt to each student depending on his or her emotions at a certain moment." All but two of the articles in the issue are closed access, but I've seen evidence of these trends elsewhere as well, and I think the editors are spot on. Image source from one of the articles.
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