By Sheridan Webb, Training Designer’s Club

To a certain extent yes, but you don’t need to be able to recite a whole list of models and theories. You definitely don’t need a learning science qualification. However, you do need a practical understanding of how people learn, and what that means for the training you design.

If you’ve been in L&D for a while, you probably already follow many sound principles: give the session a clear structure, break unfamiliar material into manageable amounts, mix up your methods, provide opportunities to practise and revisit what matters. You know these practices work, but you might not know why. Taking your understanding to the next level by knowing why these things help, makes it easier to use them deliberately, adapt them to different situations and question practices that don’t stand up to scrutiny.

Perhaps you’ve started reading around training design and found yourself with several models, competing opinions and a growing feeling that you need another qualification before you begin. I’d encourage you to consider what you actually need before committing to another qualification. It’s good to stay up to date of course – if you don’t you may still be adhering to ideas and theories that are out of date, or completely debunked – like learning styles. Instead, it’s more useful to explore why particular practices help, and whether the way you’re using them actually serves the learners.

Frameworks such as ADDIE and Nick Shackleton-Jones’s 5Di can help organise your design process. Structures like Colin Rose’s MASTER naturally build in good practice. I’ve been using them for years, but now I’ve gone deeper. Learning science helps explain why many of the practices built into those frameworks can support learning.

In this blog I explore some of the good practice you should be including in your design and WHY it works.

Start with the business outcome and the learner

Training can be interesting, enjoyable and beautifully presented without making much difference at work. Understanding the business outcome gives you something more useful to aim for than covering a topic.

“Improve feedback” could mean addressing problems earlier, making expectations clearer or helping people develop. Each would lead to different choices. Without that clarity, it’s easy to fill a workshop with worthwhile content that doesn’t solve the actual problem.

But the business outcome is only part of the picture. Putting yourself in the learner’s shoes helps you see what stands between the current situation and that outcome.

A manager may know the feedback model perfectly well but worry about damaging a relationship. Another may struggle to recognise what useful feedback sounds like. Giving both another explanation of the model won’t necessarily help.

This is why relevance means more than adding the organisation’s logo to the slides. It means understanding people’s existing knowledge, real tasks, concerns and working circumstances. Those differences influence what they need from the learning, and whether they can use it afterwards.

A clear structure and manageable chunks matter

When you know a subject well, its connections can seem obvious. For someone encountering it for the first time, they may be anything but obvious.

A clear structure helps learners see how the parts fit together. It gives them a learning journey they can follow, rather than a collection of information they have to organise for themselves.

Learners need hooks to hang new information on, and opportunities to connect it with what they already know. Without those connections, content can get lost, be harder to understand, remember and use. A clear structure can also reduce uncertainty and make it easier to follow what’s happening, including for some neurodivergent learners.

Breaking learning down into manageable chunks isn’t about making every topic simplistic or every activity short. It’s about giving people a manageable challenge and enough opportunity to make sense of it before adding more.

That’s one reason deciding what to leave out is such an important, and often difficult, part of design. Every extra model or interesting fact uses time and mental effort that could have gone towards understanding and applying something essential.

Use different methods (even though learning styles have been debunked)

The familiar claim that people learn better when teaching matches their visual, auditory or kinaesthetic “learning style” has been debunked as a basis for designing instruction.

However, that doesn’t mean every practice we developed with learning styles in mind is wrong. Some practices still hold up; the explanation for their value may be different and rooted in learning science instead. We need to consider each practice on its own merits.

For example, showing a useful diagram, allowing people time to discuss an example and giving people a chance to try something can all contribute to learning. Their value depends on what each helps people understand or do, rather than which supposed learner type it caters for.

A diagram might make a relationship clearer. A discussion might reveal assumptions. Practice might expose a gap between recognising a good answer and producing one yourself.

The point is to choose methods for a reason. Variety alone doesn’t guarantee learning, and constantly switching activities can make a session harder to follow. Ask what thinking each method encourages and whether it moves people towards the intended outcome.

Build in practice and repetition

Something can feel clear while the facilitator is explaining it, then prove surprisingly difficult to recall or use later. Understanding something at a superficial level isn’t the same as being able to apply it at work.

Practice gives learners an opportunity to turn understanding into performance. It also makes difficulties visible while there is still time to offer feedback and help them improve. That’s why a useful activity needs more than participation: it needs thinking or action that relates to what people will actually do.

Revisiting the learning matters too. There’s strong evidence that retrieval practice and spaced practice help people remember learning over time. Bringing something to mind, rather than simply rereading it, and returning to it on separate occasions can support longer-term retention.

This gives us a better reason for repetition than simply hoping a message will sink in if we say it often enough. Learners need opportunities to recall, connect and use the important ideas, including after the workshop.

That might mean returning to an earlier topic throughout the programme or looking at it against a new situation. The point is that the learner does some active work with the idea, rather than only passively hearing it again.

Leave room for pauses and breaks

When time is tight, breaks and thinking time can look like things to squeeze. But a packed agenda is only useful if people can engage with what’s in it.

A pause gives someone room to consider a question before the quickest voices fill the space. Time to reflect can help people connect an idea to their own work or recognise what they haven’t understood. This is very important to some neurodivergent learners, but actually benefits everyone.

A proper break serves another purpose: people can step away from the demands of the session, move, meet practical needs, reflect and return ready to take part. Cognitive load is finite and an activity change doesn’t always provide the mental rest that’s needed.

There isn’t one universal attention-span limit that tells us exactly when everyone needs a break. The task, its difficulty, the people and the circumstances all matter. The design judgement is to allow room for sustained effort without assuming people can keep processing unfamiliar material indefinitely.

You need useful understanding rather than a collection of theories

Many practitioners follow good principles without knowing the academic names behind them. I know I do!! That doesn’t invalidate our work. Equally, being able to name a theory doesn’t automatically mean it’s being incorporated into the design.

Understanding the why helps you judge the practice. It helps you explain why you’ve allowed time for an exercise, challenged an overloaded agenda or built in follow-up. It also helps you reconsider a familiar activity when the reason for using it no longer stands up.

Your learners don’t need to know the science behind what you do, just as you don’t need to know how an app is coded. We trust the people who design apps to know enough coding to make something that works. You need to know enough learning science to build learning experiences that work with the brains of those attending so that they can learn, retain and apply.

That’s what I explore in Brain-Friendly Training Design: A Straightforward Guide for Busy Practitioners. Written from a practitioner’s perspective, it connects findings from cognitive psychology, neuroscience and behavioural science to the decisions we make when designing training. To make it super simple to use, I’ve included a number of checklists that you can use to make sure good learning science is baked in. If you want to understand the thinking behind good practice, and use it more deliberately, take a look at the ebook here.

You can also join my upcoming Lunch n Learn, Designing with the brain in mind, to explore these ideas in a live session. Register here.

Sources and further reading

• Pashler, H., McDaniel, M., Rohrer, D. and Bjork, R. (2008). Learning Styles: Concepts and Evidence.
• Rosenshine, B. (2012). Principles of Instruction.
• Weinstein, Y., Madan, C. R. and Sumeracki, M. A. (2018). Teaching the science of learning.

Picture was AI generated and AI did help to edit the content, but it was mostly written by me.