For an educator using a web-based course delivery environment, it could be beneficial to track the activities happening in the course web site and extract patterns and behaviour prompting needs to change, improve or adapt the course... For a learner using a web-based course delivery environment, it could be beneficial to receive hints from the system on what subsequent activity to perform based on similar behaviour by other 'successful' learners.
This is from Zaïane (2001) – with 160 citations, a leading paper in the field of educational data mining (EDM), and absolutely on topic for learning analytics. So how many papers for LAK12 have cited it? None that I have seen (and, being on the programme committee, I've seen most of them).
I’m worried that we’re all so concerned with the new-minted term ‘learning analytics’ that we’re forgetting all the work in exactly the same field under the less fashionable heading ‘educational data mining’.
If pushed, we make reference to educational data mining as one of the roots of learning analytics – a root that can be handily referenced and then passed over with a perfunctory reference to Baker and Yacef’s 2009 overview of the state of EDM. We may even add another reference, or ask Ryan Baker to speak at the beginning of a MOOC. In either case, we frame EDM as the start and as the past, and go on to produce enthusiastic descriptions of a present and future that begin around the time of Educause’s discovery of learning analytics.
Are the theoretical differences so great, are the numbers working in the field so large, that the divisions between EDM and learning analytics are helpful? Or is it that we want to be academic analysts, not plebeian miners? Are we avoiding the established EDM journal, conference and society because they have little direct relevance to us, or is it that we’re too busy describing new projects to potential analytics funders to spend time investigating the years of work that has already been done?
I’m worried that we’re all so concerned with the new-minted term ‘learning analytics’ that we’re forgetting all the work in exactly the same field under the less fashionable heading ‘educational data mining’.
If pushed, we make reference to educational data mining as one of the roots of learning analytics – a root that can be handily referenced and then passed over with a perfunctory reference to Baker and Yacef’s 2009 overview of the state of EDM. We may even add another reference, or ask Ryan Baker to speak at the beginning of a MOOC. In either case, we frame EDM as the start and as the past, and go on to produce enthusiastic descriptions of a present and future that begin around the time of Educause’s discovery of learning analytics.
Are the theoretical differences so great, are the numbers working in the field so large, that the divisions between EDM and learning analytics are helpful? Or is it that we want to be academic analysts, not plebeian miners? Are we avoiding the established EDM journal, conference and society because they have little direct relevance to us, or is it that we’re too busy describing new projects to potential analytics funders to spend time investigating the years of work that has already been done?
Rebecca, this post helped me uncover some publications on educational data mining and academic libraries. Not many, mind you, but I hadn't found many at all using "learning analytics." So, thanks.
ReplyDeleteHi Rebecca Ferguson,
ReplyDeleteI think your comment comes at the right moment. While I'm reading papers about Learning Analytics and Educational Data Mining analytics, I am wondering why there is no cross-references between the two disciplines despite there are more similarities than differences. I also wonder what are the differences that lead them to different paths. Thanks
Hello Rebecca and Fernando,
DeleteI share the same thought, adding that seems to have a third "name" (Academic Analytics) that deals with the same questions in a slight different perspective. Maybe it should be extremely valuable to unite forces among those three groups, in order to create a single field that would provide the fundamental framework and political support for the broad implementation of Analytics in Education.