learning analytics

A vendor view of Learning Technologies 2017

Reading Time: 5 minutes

I spent two days last week at the Learning Technologies 2017 exhibition, working on the LEO stand (below). This annual event is split over two floors, with a paid conference upstairs and free exhibition downstairs. The stand was really busy for both days and the whole team came away absolutely exhausted, but I did manage to wander around the exhibition looking to see what the trends were this year and seeking out interesting new products.

Algorithms and echo chambers in the world of learning

Reading Time: 3 minutes

There has been lots in the news this past year about social media bias and echo chambers, which started gaining prominence when algorithms started meddling in your news feed. The major web companies collect a huge amount of data about you and in doing so are building a detailed profile comprising demographic data, likes and purchases and other data that has been captured and purchased. As you ‘like’ posts and pages, so the algorithm delivers similar content back to you. Your friends like certain things, or ‘people like you’ like certain things, and the algorithm delivers more of that content to you too. You search for and purchase certain things, and you get delivered content related to that. Maybe you even give away valuable data via an innocuous-looking Facebook quiz,  which is then sold to highest bidder and fed into yet more algorithms to target you with stuff you might ‘like’.

Building a learning analytics platform

Reading Time: 4 minutes

As learning analytics continues to rise up the agenda in the corporate learning & development (L&D) sector, one thing is becoming glaringly apparent: we should not expect a one-size-fits-all, off-the-shelf approach to learning analytics.  This is a specialist discipline that cannot be bottled up into a single product. Sure, there are products such as Knewton, a Product as a Service platform used to power other peoples’ tools. There are also LMS bolt-ons like Desire2Learn Insights or Blackboard Analytics but even they are not sold as off-the-shelf products, for example the Blackboard team “tailors each solution to your unique institutional profile”.  There are just far too many organisational factors at play for an L&D practitioner to be able to implement a learning analytics programme using an off-the-shelf tool.

xAPI Barcamp – a Learning Technologies fringe event

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The xAPI Barcamp at the end of the first day of the Learning Technologies conference attracted around fifty people, eager to talk xAPI over a few free drinks at the local pub! I was one of five invited experts alongside Andrew Downes from Rustici (@mrdownes), Mark Berthelemy from Wyver Solutions(@berthelemy), Ben Betts from Learning Locker (@bbetts) and Jonathan Archibald from Tesello (@jonarchibald). Moving around five tables in turn, each expert began by talking for a few minutes about what they were doing with xAPI, then the table held an open discussion.

Data science: the new skillset for learning technologists

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For all the talk of big data being the next big thing in learning technology, few people mention that in workplace learning there just aren’t any examples of big data to speak of. The data collected just isn’t at the same scale. However, big data has led to an explosion in data analysis tools and techniques that learning technologists can use in their work. Throughout 2014 I’ve been dipping into data science MOOCs, learning the basics of R programming, and thinking about how to apply this within learning and development. These are some of my initial thoughts and notes.

What we can learn from the ephemeral web

Reading Time: 4 minutes

Learning Platforms have flourished in the past decade, and as they have scaled with the rise of MOOCs, the data inside them has also become increasingly valuable. Different people see different value in this data. Some want to analyse data to predict outcomes and trigger early interventions when needed. Others want to analyse large datasets to advance machine learning techniques. Many more just see dollar signs in anything related to ‘big data’ so, in true startup fashion, they start collecting huge quantities of learner data now in anticipation of monetising it later.

Re-entering the world of MOOCs at LAK13

Reading Time: 3 minutes

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So, here I am on the Learning Analytics and Knowledge MOOC again, or LAK13 to use its abbreviated name. It is one full year since I aborted LAK12 and 18 months since I aborted the famed Stanford AI MOOC. Determined not be a perennial MOOC dropout I have decided to have another crack of the whip. Not that being a MOOC dropout is necessarily a bad thing, at least not in my book although the MOOC bashers will no doubt beg to differ. People will enter into open courses for many reasons and the success of a MOOC shouldn’t be determined by the number of finishers. I gained a lot from LAK12 in the limited time I was on it and it gave me a great primer on learning analytics which has been really useful in my work over the past year.