I’m not sure everyone will agree with me, but I have this theory about our eLearning industry. My, entirely personal, view based on the completely unscientific sample of what I have seen and heard over the years is that we take to new technology just that shade suspiciously. Once the initial acceptance is in place, though we go about adopting it quite enthusiastically. A glance at the adoption curve of mLearning will probably substantiate what I mean. There is another technology trend that has been sweeping the world for a few years now but has only just started appearing more commonly – big data in eLearning.
Big Data: Set to Make a Big Impact in eLearning
“eLearning is changing. And, we will see new models, new technologies and designs emerge. So let’s drop the “e”; or at least give it a new or wider definition.” – Elliot Masie, Author & eLearning expert
An IDG study in 2015 revealed that 80% of enterprises and 63% of small businesses had either already deployed or were going to shortly deploy Big Data initiatives; it’s fair to say that Big Data has well and truly arrived in the enterprise! As a general rule a lot of data about learners and their interactions with the courses we create is available (or, at least, is collected!). Assuming the willingness to leverage the insights hidden in this data exists, where can the greatest impact be felt in eLearning though?
The use of Big Data in the HR space within organizations is becoming increasingly common. Among the ways this data is being leveraged is to proactively identify the likely learning needs of specific individuals, teams or even larger business groups and to recommend when and how they should undergo what specific training course.
What Instructional Designers and course creators are likely to find most valuable, though is the insights they can get from Analytics (what’s Big Data without Analytics?). Hidden within all the data on learners and how they interact with the courses is actionable information aplenty. Would it not be valuable to know which modules and which specific portions within those modules are dragging down the effectiveness of the overall learning? Looking at aggregate data over a large number of users and even courses could suggest specific strategies for improving learning effectiveness. For e.g. there is a large number of learners scanning through videos in “fast forward” without negatively impacting learning outcomes – consider including shorter, bite-sized videos in your course then. Leveraging the insights on effectiveness, learner preferences and usage patterns will allow all of us to define learning strategies that are more in tune with what is more likely to work for the audience we are looking to address.
How about predictive analytics? What has gone before could offer you insights into what is likely to occur in the future – hopefully to allow you to prepare better. An example I have seen quoted is that of the American Public University System that has managed to reduce student dropout rates by as much as 17% by identifying students on the verge of leaving and then putting some remedial action into play. The point here is if you have a sense of what change has to be made you could do it – save time and of course, improve effectiveness.
An area that I am personally excited about is personalization. Think about how when you go to Amazon the page you land on seems almost tailored to your tastes specifically. There are recommendations that align with your preferences, information on what your friends are buying or what other people like you are likely to have chosen, reviews of products that you have googled and so on. This degree of personalization is driven by the power of Big Data and Analytics – no reason why our courses should not be similarly “tailored” to the preferences of specific learners. I believe that personalization could be a big help in winning the “engagement” battle – isn’t that one windmill we have all tilted against for years?
In closing let me make the point that technology is, at best, a tool but Big Data seems to be too big a gun to ignore for long. My own view is the adoption of Big Data will skyrocket over the next couple of years – change is inevitable. Wasn’t it Jim Crapko who said, “If you continue training the same way you’ve always trained, don’t expect to get better results.”