It takes a lot of reading to get to this point, but here's the outcome: "Learning Analytics (LA) papers focused more on student engagement, teaching tools, and social network analysis whereas educational data mining (EDM) papers focused more on techniques and methods of data analysis." The bulk of this paper (14 page PDF) is devoted to a description of the paper selection process, topic-modeling methodology, and discussion of the results. The lists of topics for the two types are almost identical, with only expected differences ('mining' vs 'analysis') in the ordering of the topics. The authors also point to areas overlooked by the two types of papers - "disciplinary blinds spots such as big data and AI ethics" - and suggests "they ought to focus on theory and knowledge building." The last thing this discipline needs is Yet Another Theory, but hey, who am I to talk?
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