All learning experiences, no matter how well they are designed, are flawed.

It saddens me to admit this but it’s true.  We can’t create ‘the perfect’ learning experience but what we can do as practitioners is increase the likelihood of learning occurring (and mitigate the many factors that influences how anyone interacts with them).

After a chance meeting with Laura Watkin in June 2019 at @HallamEdFest, we have for one reason or another continued connecting.  Last year we realised why.  It’s because we both are determined to ‘solve’ the puzzle of designing effective learning.  We want to make the ‘science of learning’ more accessible, not just for our own work, but also for our fellow practitioners so that we can all increase the likelihood of learning occurring.  We’ve built up considerable knowledge between us but are not trying to become academic experts – those experts already exist (and we will be drawing upon them).  What we recognise in each other is an opportunity to harness our combined strengths in communicating and engaging with others, to share the insights we’ve uncovered and the success we’ve already had in our own work as a result.

We have spent the last 12 or so months conceptualising a model for ‘learning design’, something that captures what we believe to be ‘good science’ in this space and then present it in a way that’s accessible to any audience.   The accessible part is really important to us as the science behind learning isn’t simple (don’t we know it!) and we didn’t want to lose the complexity and nuance from the research or fall into the many traps of misapplication.   However, we recognised that there are still far too many great people and organisations who don’t know enough about learning and struggle to connect with evidence-informed practice.  The travesty is that even a small amount of extra knowledge could be a game-changer for so many in terms of impact.

It’s time to share where we are at… this is our #WorkingOutLoud.  In considering this we need you, the reader, to recognise:

1. This is not a fully formed or finished idea (whilst the concept is strong in our minds we are still very much working on this as we learn and iterate)
2. This blog in itself is unlikely to adhere to some of the principles we advocate (purely because we are in a sense-making and broadcast/transmit phase of development)
3. We may not have all the dot’s lined up (but because of this we are excited as it means there is more for us to do/learn – perhaps you’d like to join us on this journey?).

The model, which we will summarise here consists of 4 key principles:

1. Attention – what is not attended to is not learnt, so how may we gain, direct and maintain attention on what’s important?
2. Sense-making – what is not understood is discarded, so how do we afford for meaning generation?
3. Retention – what is not recalled can be lost, how are we supporting accurate retrieval?
4. Internalisation – how do we make new learning part of our being and shape our behaviours without decay?

This model right now has the very cool acronym of ASRI (pronounced Ass-ree) which being honest, Laura is not thrilled about! But before we get clever with the marketing and labelling of things we wanted to get the science in our story right and we’re confident we’ve got solid foundations on which to build. We hope a catchier model name will come to us as we work through this process.

Why these 4 and not the many others?

I’m not going to go through why we have selected these four principles over the many that we could have, other than to say we feel most other ‘Learning Science’ methods and approaches fit within these or align to them.  The model also had to make sense to us, and reflect that myself and Laura are creating this based on a balance of our personal experience as learners, our experience as learning designers and our knowledge gathered (and still being gathered) during our self-directed and professional research. And our appreciation for the contexts in which we do our work.  We are committed to thinking about application and are always asking ourselves “what does this look like in practice?”.

The Science of Attention

Helping learners ‘pay attention’ is central to the learning process.  As scientist unravel the mysteries of the brain, and test what it chooses to attend to, what it monitors and what it ignores we get closer to being able to build attention strategies.   Attention is much more than simply ‘noticing’ something; it’s about how people perceive, attach significance and filter out.

Who’d have thought there were varying categories of attention, when I first started looking at this I saw it as you either attended to stuff or you didn’t. How naïve, I now know that attention is not a single process but a group of processes including:

• Arousal (high or low) – the state we find ourselves in (e.g. excited, alert or not)
• Focused Attention – here we have locked into something. But what’s the cognitive energy cost?
• Sustained Attention – this is prolonged attention over time. But how long can we be attentive for before mind wandering occurs or we need a break?
• Selective Attention – here we attend to some stuff while ignoring others. But how good are we at attending to the right stuff or filtering?
• Alternating Attention – this is a rapid switching of focus from one task to another. But what’s the impact on the quality of learning?
• Divided Attention – this is attending to more than one thing at a time. Can we actually do this?

And then there’s ‘in-attentional blindness’ – missing the obvious in front of you (like an unexpected stimuli in plain sight) while attending to other stuff!

The reality being ‘paying attention’ is the first step in the learning process and we the practitioner need to a) help learners attend to the pertinent stuff and b) help them filter out the irrelevant. Therefore, in studying attention we must also consider our nemesis – distraction and misdirection (something we are looking at with those who are the experts – in this case what better experts can there be than magicians and illusionists?).

The Science of Sense-Making

OK so we have peoples’ attention, now what?!!! I, like you and many others, have found myself in receipt of information, insight and experiences that I could not place, understand or appreciate. When this happens we often discard it or if we try to hold on to it we cannot retain it for long. For it to stick with us we need to be able to make sense of it and attach personal meaning to it.  With this in mind it’s important I share a couple of definitions which will guide our thinking in this space:

Sense making – refers to how we go about creating meaning from the new information we’ve received.  A situational awareness and making sense of the information in the world around us so we can make decisions and act within it.

Meaning making – refers to how we interpret situations or experiences in relation to pre-existing knowledge/events. An understanding of ‘self’ in relation to the new information and world around us.

So – ‘sense making’ is about making sense of information in the ‘external’ world – what’s going on out there? Meaning making is about relating this to our ‘inner’ world – what will this mean for me? It seems quite simple but, when we present new information to people they will ask two basic questions before attempting to commit it to long-term memory:

1. Does this information make sense? Yes = Keep, No = Discard (or attempt to sense make)
2. Can I attach meaning to it? Yes = Keep, No = Likely to Discard (or attempt to find meaning)

The questions then to us as practitioners are – how do we help people to sense make? How do we help people to connect meaning to new learning?

Well that’s where ‘generative learning approaches’ come in. The technical definition goes something like this – Generative learning involves the active integration of new ideas within the existing. Drawing lines (which may be dotted at first) between pieces of new and existing material. Some of the most popular strategies include concept mapping, explaining, predicting, questioning, testing and drawing. These are all about building relationships between new info and stored info, giving personal meaning to this (i.e. what does this mean for me in my context?). Our nemesis here is confusion and disconnect.

The Science of Retention

Helping things stick…. We’ve made sense of it and we have personal meaning for it but how do we keep it? Retention relates to strengthening those dotted lines, making them solid and thicker and multiple. Fixing things in our long-term memory. But we don’t just want it to sit there we want it to be easily retrieved.

Here, we would do well to get our heads round key ideas like ‘interleaving’ and ‘retrieval practice’ – when neurons are frequently fired (in the recall of memories) synaptic connections are strengthened (our dotted line of connection becomes thicker). In ‘calling previous information to mind’ we bring it into our working memory and give opportunity to improve the meaningfulness of this. However, we also give opportunity for memories to be modified. See memories are not stored as ‘a whole unit’ but as fragments located within different parts of the brain. As we bring these memories back together and re-construct them they may change! (we possibly adapt them – wrongly).

In the process of recall we can build strategies in our favour by adding sensory layers to memories including smells, texture, sounds and vivid descriptions etc., increasing the salience and depth and connectedness of a memory. The trick around retrieval practice is getting the gap right, the one between learning new stuff and the point of recall? This is not an exact science….

Our nemesis here is, transience. The impermanence of memory due to poor encoding and lack of retrieval. The human brain is kinda designed to forget. It’s an evolutionary strategy, running in the background discarding information no longer needed or stuff that’s rarely retrieved.

The Science of Internalisation

Our desire at this point is to ensure new learning has become part of who you are.  Experiences, knowledge and skills are all now within you. Genuine learning has occurred and the capacity for improved performance has been increased because you’re acting with the influence of the new information you acquired.

Here internalisation refers to the process through which we learn and absorbed new stuff about the world around us. It’s the deepest form of learning.  We have changed.  Or at least the configuration of our neurons have.  The dots we connected through our generative learning activities have been bound to our internal systems through retention strategies. This new learning has been transformed into an ‘intrapersonal’ (within self) asset.

When this has occurred, retrieval fluency is high (the ease with which information comes to mind). We are able to confidently and accurately recall information, experiences and skills automatically (like a reflex). This frees up our brain capacity to attend to other environmental cue’s/stimuli. Our nemesis here is memory decay/distortion. Although the practice of ‘overlearning’ (rehearsing beyond the point where we no longer improve) could help us here.

In Closing

So there you have it… our early thinking on a model for ‘Learning Design’. All of the above will be checked, tested and evolved before we launch anything. Oh and it will be evidence based.

Call to Action

We are looking for a ‘sense-making’ group of peers across sectors that would be happy to offer their time freely in exchange for being part of an awesome group of humans who will do the testing and retesting of our thinking (and be a fundamental part of an iterative process). What do you get? We expect that we’ll all learn loads from being part of this, we believe it will be enriching for all involved and an opportunity to network and share stories.  If you are keen send us your desire to kurt@bemorelnd.co.uk  or use the contacts form

Thanks for reading.

Big love all Kurt and Laura