The twinning of EDM and Learning Analytics


After listening to Ryan Baker’s presentation on Educational Data Mining (EDM), I am more convinced than ever that EDM and Learning Analytics are actually the same side of the same coin. Despite attempts being made to explain them into different zones of influence or different missions, I fail to see such differences, and from reading other LAK12 participants’ reflections, I am not alone in this. Baker’s view that Learning Analytics are somewhat more “holistic” can be refuted with a simple “depends”. What is more, historically, EDM and LA don’t even originate from different scientific communities, such as is the case with metadata communities versus librarians, or with electric versus magnetic force physics – now of course known as electromagnetism.

Both approaches (if there are indeed two) are based on examining datasets to find ‘invisible’ patterns that can be translated into information useful to improve the success and efficiency of the learning processes. A good example Baker mentioned was the detection of students that digress, misunderstand, game the system, or disengage. It’s all in the data.

I would also like to believe that predicting the future leads to changing the future, at least it could give users the air of being in control of their destination. As a promotional message this has quite some power. But even in support of reflection the same can be postulated: knowing past performance can help your future performance! So, once again a strong overlap between predictive and reflective application of data analytics.

For me, all of this can only lead one way: instead of using efforts and energies to differentiate the two domains, which would only lead to reduced communities both ends, and friction in between, we need to think big and marry them into one large community and domain: Let’s twin EDM and LA!

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One response to “The twinning of EDM and Learning Analytics

  1. Ryan Baker 12/02/2012 at 06:42

    It’s interesting. I’ve read a lot of perspectives the last week saying this from folks who attended my session. I’ve heard this same perspective since the LAK conference emerged last year, from folks on both sides. But if they are the same thing, why did two communities emerge? Why didn’t LAK folks just join EDM, the older conference? Why is there a relatively small overlap in attendance between the two conferences? It must have been — at least in part — because the LAK founders didn’t see EDM as what they were doing. It’s certainly not out of friction; the leaders of the two communities get along very well.

    Seeing the work that appears at each conference, I don’t think they *are* the same thing. There are many commonalities, but there are important differences as well. And that makes it a good thing to have two communities. Different scientific communities respectfully arguing for different ways of looking at the same phenomena is one of the best ways of arriving at truth. As long as we can keep the argument friendly, and learn from each other, everyone will win in the long-term.

    The alternative, some sort of forced merger, would almost invariably reduce the diversity of scientific ideas and perspectives in this space. We’re way too early in the science of educational/learning data to do that. We need to try out different perspectives and standards.

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