What are learning tech orgs really doing with personalisation?

Our Content Marketing Executive (and social media supremo) Lauren Keith reflects and expands on a recent Twitter conversation: when we talk about personalised learning solutions, what do we really mean?

The other Friday, as part of the usual pre-weekend Twitter burst, I found myself in an interesting conversation with @LearnPatch. Talking about what personalisation in learning really is, the L&D start-up company commented honestly and candidly:

It’s not untrue: When it comes to personalisation, learning organisations haven’t exactly delivered the Amazon/Google customer-targeting treatment. We rarely have the multimillion-dollar budgets to play with, nor the huge masses of user data to mine for insight-driven personalisation. But whilst we’re getting closer to the latter, that’s not to say we’re not tapping into personalisation in other ways.

From behind the Brightwave account, I thought about my reply. But short of ‘Not entirely but no space to explain – soz!’, how do you reply honestly within the confines of Twitter? Naturally, I didn’t cover everything I wanted to. I’m now out to provide a more complete response – or at least one that breaks the 140 character barrier.

So… What are we doing to support a personalised experience?

First, let’s look at what we mean by this. Personalisation means to cater to the individual – essentially, serving the right content to the right person, in the right format, at the right time and in the right place – and there are endless ways of approaching this. It doesn’t have to mean big data, big investments and artificial intelligence. It can all be in the design.

Branching videos

This technique pays homage to the ‘choose your adventure’ type storybooks you might have read as a child: The learner gets to make a choice as to how the narrative will play out, with their answer affecting what happens next and the final outcome of the story. Except instead of chapters, the whole thing is done in a handful of short video clips.

Last year we worked on a project with Diageo for bar ‘mixologists’, on how to best mix and serve cocktails. Here, from the point of view of the mixologist, the learner is presented with a number of short decision making scenarios around serving their customers. For instance, what to do when a new customer is waiting whilst you’re still serving someone else, or which glass or technique is required for which cocktail. The answer given by the learner would determine which piece of video would follow, demonstrating the effect of their decision – a happy customer, a disgruntled customer and so on. In some cases, it would also affect the sequence of the narrative and subsequent decision making.

Of course, interactive videos aren’t a new thing. But with better tech, new interactive enhancements, and more creative approaches available than ever, companies have been able to explore new ways of developing interactive video solutions that are unique to everyone who plays them.

We’ve also been gamifying some of our interactive videos by introducing playful scoring systems: at the end of the video narrative, the learner’s success may be verified by quantitative measurements such as the amount of budget they have left, lives they’ve saved or problems they’ve adverted. This is a neat way of tying together the learner’s individual story with measurable, testable feedback data.

We’ve also recently developed an interactive video sequence in which the learner controls the speed the video is played at by using their scroll button – another way of putting the content delivery into the learner’s hands.

Custom scenario games

When bandwidth, budget or content don’t lend themselves to video, there’s still scope to be inventive with interactive branching scenarios. We have recently developed an immersive text-based game engine to create gamified scenarios. One of our clients is the international Anti-corruption Resource Centre ‘U4’ who deliver online and face-to-face training on reducing corruption for international development NGOs.

Like with the branching videos, the learner is asked to make a choice at a number of stages which may have a knock-on effect on the next stage – and the final result. But instead of video clips, the story plays out with animated text.

In the U4 course, users play the role of ‘Task Manager’, whose country has allocated $100 million to improve the healthcare situation in their region as part of a donor program. The idea is to save as many lives as possible, while avoiding corruption and staying on schedule.

They are asked a series of questions about how to best spend the money and react to some spanners in the works. Their answers might affect the next stage of questioning. For instance, the choice to accept a small act of non-compliance early on might result in a larger issue later. Or choosing to stick rigidly to compliance rules may create resistance in certain groups. Below is an example of how the answer to one question can affect the next line of questioning.

At the end of the scenario, they find out how many lives they’ve saved and how much of the budget remains.

Interactive custom scenarios – be they video, text or otherwise – are a fun and engaging way of supporting personalisation. The learner steers the story and determines the ending, making it personal to their preferences, their understanding and what they would do in that situation.

Most crucially, this kind of approach highlights the gaps in the learner’s own knowledge – it adds real data towards a picture of where their own learning journey should go next.


Another way of adding a personal touch to story-based learning is by using avatars. Done simply, this is when you choose an avatar at the start of the course who then is your ‘protagonist’ within the course, or your ‘guide’. This is something we’ve all seen in eLearning courses throughout the last ten or twenty years. But with a little creativity, these can play a much bigger part in personalisation than they did in the 1990s.

For example, content can be adapted to suit the character of the chosen avatar. In a recent course on technological risk, each avatar had a different attitude to risk. As a learner you could choose an avatar that reflected your own attitude and see how that affected the story thread through the course.

Learning pathways

Here’s where we start dealing more in data and thinking beyond single eLearning courses.

Learning pathways are collections of small learning components – courses and materials – that can be tailored to suit a learner’s individual needs. Here at Brightwave, we use our collaborative learning platform – tessello – to host learning pathways. Below is an example of one of my own learning pathways, designed for providing great customer experiece.

Managers and administrators can tailor-make learning pathways for particular groups – inductees for example. Alternatively, they can be served based on a diagnostic: The learner may be given a pre-learning questionnaire which determines their level of current knowledge, their learning requirement and, subsequently, which learning pathway(s) they’re served.

Learners can pull in content to their learning pathway to show their progress and leave comments for their manager who, in turn, can feed back and coach when it suits them. It’s data driven personalisation that supports around-the-clock, multi-device learning.

Course diagnostics

But diagnostics can, of course, also work inside the boundaries of a single piece of eLearning. Take role filters for example: Upon launching a course, the learner will fill in some questions about their job role to determine which elements of the course they see.

Moreover, using simple design techniques like unlocked topics and quizzes, we can allow learners to skip straight to a course quiz, should they want to bypass the learning content. In this way, the course is open to support learners of all levels and learning needs.

So that’s what we’re already doing with personalisation. Or at least that’s the stuff we can tell you about right now…

When the right project comes along, we’re looking to do bigger. That could mean big data, big engines and big diagnostics. But let’s not forget ourselves – It’s not always the size that counts.

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