Custom learning production: Moving to the next level – and taking everyone with you

In this blog – based upon a presentation given at a recent Learning and Skills Group webinar – Brightwave Group’s Director of Operations Fiona Nunn looks at the problems associated with creating personalised learning content for large numbers of learners – and what we can do to overcome them…














What is Personalisation?

In today’s media ecology personalisation – also sometimes called custom or bespoke content – refers to anything that we feel has been created or adapted for our individual needs or desires. This understanding of the *feeling* of personalisation is important: personalisation can be just as much a subjective impression within the learner as a product of bespoke, custom-engineered content.

Why is it useful in a learning context? There are three clear chief benefits:

  • Personalisation engages – learners take more notice and learn more efficiently if the content they receive is tailored to their specific, individual needs, focused and relevant.
    It’s more than just having the right tool or learning resource for the right job. There is a huge psychological factor involved too – personalised content appeals to our individuality and draws us in.
  • Personalisation saves time – most learners are time poor, and everyone is information rich – almost too rich! We don’t have time to search for relevant learning content.
  • Personalisation saves money – see above: as the saying goes, time is money! But personalised learning content – taking that sharp focus – stops us wasting resources producing content that people will not read, engage with or learn from.

Today’s most innovative content brands – from Amazon to Netflix – learn what we and people like us like to read or watch, and give us recommendations that are relevant – the accuracy and predictive power of these suggestions increase the more we engage with the content.

These processes invite us to participate in and contribute to a virtuous symbiosis with the brands and the content they offer us – the more we give to them, the more we get back.

The desired outcome for both parties is the production of the all-important AHA! moment – where our particular need at a particular time is met with the perfect piece of content – almost before we realise we want it. The content is perfect, but our impression of the brand is boosted too. We don’t just like what we see – we also come back for more. And the more this happens, the more AHA! moments we get.

It’s easy to see from this why pursuing personalised content would be of particular use to anyone producing learning content – the AHA! moment is exactly what every educator has been trying to elicit from their learners since time immemorial.

But there are unique challenges around the creation of personalised learning content that broader content brands don’t have to consider. There are currently three viable forms or levels of personalisation:

  • Basic
    Automated but superficial alterations to the visual appearance of learning content: the creative use of simple LMS functionality. This makes the learning ‘friendlier’ – gives it a form the learner is more likely to respond to.
  • Customised
    Driven personalisation within a course, with intelligence provided through a set of initial questions that diagnose and focus on the learner’s individual requirements.
  • Adaptive
    A smart system which makes inferences from your past behaviour, job role, user profile, peer data etc. and adapts to deliver appropriate content. It learns about what you know and what you want as you engage with the system.

There are no bounds to what we might be targeted with in the future. We can take adaptive learning several steps further and imagine a system that knows what you’ve already learnt, knows what sort of content you are interested in, and also knows what the next steps in that learner journey might be for you.

Throughout your day it makes suggestions of what you should learn next – but it knows how you prefer to take your learning at different times of the day. So it suggests a short learning game when you are on a train – because that’s when you normally like to play games. It suggests an article to read when you are having coffee in your favourite café, because that’s when you like to read long-form text pieces.

Meanwhile, back on planet Earth, what is feasible and realistic for personalised learning content, given current budgets, technologies and learning needs?

Personalised learning is often a supplement or enhancement of generic, often mandatory learning courses, where a top level path of general information opens out more specific, in-depth or technical content. This can be achieved with a smart learning diagnostic that interrogates what the learner already knows and serves up learning resources to fill their current knowledge gaps.

Similar effects can be achieved by having the learner pre-select their own path from a number of given, pre-selected options – this is the equivalent of picking an off the peg suit that has been cut to the specification of someone very like you – but not the same as going to a tailor and having a suit made to your exact personal measurements. Requiring less sophisticated machine intelligence, it engages the learner and helps them absorb and act upon their learning, but is less likely to produce the AHA! moments that delight the learner, and drives them to ever greater learning, innovation and achievement.

Read part two of Fiona’s blog on the Brightwave website.

Follow Fiona on Twitter.

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