Algorithms and echo chambers in the world of learning

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’.

The resulting and widely-discussed ‘echo chamber’ means people seeing content that mostly just panders to their existing world view, whatever that may be. With increasing numbers of people now consuming news through social media alone, this results in people being less challenged, less exposed to other opinions and events,  with their views becoming ever more polarised and entrenched.

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Building a learning analytics platform

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.

What a learning analytics platform looks like

OUAnalyseAn example of one platform (not a commercially available product but probably the most advanced learning analytics platform I’ve yet seen) is the Open University’s OU Analyse platform. They demonstrated this at MoodleMoot UK and Ireland recently. The product is very geared to the OU’s own Moodle-based VLE and as such is built to answer their own questions. This  predictive analytics platform analyses demographic and course data from their own VLE with a view to predicting which students are likely to fail. Tutors have a login to the system and can use the dashboard tools to determine which learning interventions to recommend to a student in order to get them back on a path to success.

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MoodleMoot 2015 Review

This year was my fourth Moot and it was another cracking event. Dublin is a welcoming and accessible location so it was good to be back here. I attended the two conference days on May 12-13, but the conference was topped and tailed by a workshops day on the 11th and a developer hackfest on the 14th.

First ever workplace learning stream

Of particular interest for me was that for the first time the conference featured a workplace learning stream. Despite Moodle topping multiple surveys of the the most widely used workplace LMSes, previous Moots have typically been dominated by the education sector. It’s great to see the focus gradually shift and the conference become more representative of real world Moodle users. It was nice to hear Moodle HQ presenters reinforce that future Moots would be structured along similar lines.

The workplace stream consisted of case studies from:

  • Civil Service Learning
  • University Hospital Southampton
  • Health and Safety Authority
  • An Irish law company
  • A US Healthcare company

There was also a good analysis of the business impact of long term support vs yearly upgrades from the conference organiser, Gavin Henrick. The workplace stream was well attended, and I look forward to more of the same in future years! Continue reading “MoodleMoot 2015 Review”

Data science: the new skillset for learning technologists

Coloured_GraphFor 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.

Can understanding big data techniques help us to improve learning outcomes and performance?

Big Data as a term started appearing following the success of online services such as Facebook, Google Search and Twitter which gather data on hundreds of millions of people. Data including their likes and dislikes, online behaviours, website usage patterns, shopping patterns; it all has value and can be sold to the highest bidder. Now that users can also register for other online services using their Facebook, Twitter or Google logins, they literally leave a trail of ‘digital exhaust’ behind them. This data is all collected and analysed on the assumption that it is valuable to someone, somewhere, or at least may be one day. The data gathered by just one service like Facebook amounts to over 500 terabytes per day! This is the scale that big data operates at, and the harvesting of personal data is BIG business. Jaron Lanier is not wrong in suggesting that next time you post a status update, they really should be paying YOU!

Edtech and learning technology entrepreneurs clearly want a slice of this action, hence the buzz. However, even the largest organisations only have relatively small amounts of learning related data. Even an organisation with half a million employees will only have learning related data measured in little old Gigabytes. That’s not big data at all.

However, if there is one big takeaway from the big data world then it is the renewed focus on data analysis and data driven insights. Take a look at any MOOC catalogue to see the popularity of data science courses. Continue reading “Data science: the new skillset for learning technologists”

What we can learn from the ephemeral web

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.

But the learning technologies world needs to be mindful of the increasing unease among consumers about the storage of personal data by software providers and organisations, particularly among Millenials. Common concerns centre around data privacy issues, the ethics of amassing huge volumes of personal data, the exploitation of users by those collecting data, excessive government monitoring of citizens and the permanence of stored data.

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Re-entering the world of MOOCs at LAK13

IMG_20130227_205107So, 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.

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