In the last article I explained Illeris’s Two Basic Processes of Learning. In this article, I will introduce his Three Dimensions of Learning, which naturally follow on.
The three dimensions are a powerful tool for analysing and improving a learning process. If you find that you’re giving your learners good content, but it’s not landing like you expect, this framework can help. It is particularly useful if you know the content is good because it has been used successfully before but it’s not working now for some reason.
I will begin by discussing the three dimensions according to Illeris’s diagrams and descriptions. Next, I will introduce what I believe is a better way to illustrate this framework, along with a tool that you can use to analyse learning situations. Finally, I will again discuss the relevance for tech education.
The three dimensions
First, let’s look again at the two processes.
Illeris’s elaborates as follows:
The two double arrows can now span out a triangular field between three angles. These three angles depict three spheres or dimensions of learning.1
This is how Illeris diagrams this triangular field:
I find this diagram somewhat hard to process. My first thought is to plot things in this space — for example a particular learning interaction, or technique, or aspect. However, since practically everything combines these aspects in complex ways, this is quite a confusing thing to do.
I’ll propose a solution to this problem shortly, but first — let’s look at each of the dimensions:
The Content dimension
The content dimension concerns what is learned. This is usually described as knowledge and skills, but also many other things such as opinions, insight, meaning, attitudes, values, ways of behaviour, methods, strategies, etc. may be involved as learning content, and contribute to building up the understanding and the capacity of the learner. The endeavour of the learner is to construct meaning and ability to deal with the challenges of practical life and thereby an overall personal functionality is developed.
In the diagram above, we can deduce that Illeris has put the concrete instances of ‘content’ beneath the arrow, and the loftier goals above. The goal of building up mental content (e.g. knowledge) is to make sense of your world (meaning) and be able to do new things successfully (abilities).
Note again that we should not confuse content for material. This article is not content! The concepts you are drawing on and building in your head as you read it are content.
The Incentive dimension
The incentive dimension provides and directs the mental energy that is necessary for the learning process to take place. It comprises such elements as feelings, emotions, motivation and volition [the use of will]. Its ultimate function is to secure the continuous mental balance of the learner and thereby it simultaneously develops a personal sensitivity.
The basic view of this is that feelings and motivation are involved in learning and need to be in a position of ‘health’ in order to learn. However, Illeris has used some unfamiliar terms here — what is ‘sensitivity’?
Here, I believe Illeris is referring to something bigger than just wellbeing. Consider this question — how well do you feel you are understanding me right now? Perhaps you feel a little confused, or maybe it’s perfectly clear, or obvious, or it’s sparking other trains of thought.
In considering that question, you probably didn’t think “well, I suppose I ought to go and test the concepts in my brain against reality in some way”. Those ‘sensations’ of understanding, confusion, distraction, already existed. This battery of sensations is tightly woven around cognition.
Let’s imagine for a moment that you lost the ability to feel confusion — how would that alter your effectiveness as a learner? Perhaps for the worse! Because you use that sensation to direct mental effort towards those areas in order to achieve better understanding.
One further point of interest — learners often make mistakes about their degree of understanding. If you are a teacher you will know this well — think back on all of the times you have been certain you understood something until a student asked you to explain it!
It is this dimension — including both broad emotions, goals, fatigue, and the microcosm of cognitive sensation amongst other things — that I believe Illeris refers to as ‘Incentive’.
The Interaction dimension
The interaction dimension provides the impulses that initiate the learning process. This may take place as perception, transmission, experience, imitation, activity, participation, etc. It serves the personal integration in communities and society and thereby also builds up the sociality of the learner.
All learning happens in interaction with the world — whether that’s the computer failing to run your code, or your teacher explaining a complex concept to you.
It’s fair to say, however, that Illeris’ focus here is on the social world. In a way this is limiting — but in another way it is a useful reminder that we are all social beings and a great deal of our life involves interacting with others. Ultimately, the job to which most learning is put is to help the learner find and fulfil a role in her society.
As such, while we can challenge Illeris’ neglect of the non-social environment as a contributor to learning, we can’t doubt that the ultimate direction of learning is in nearly all cases social.
[The content and incentive dimensions] are always initiated by impulses from interaction processes and integrated in the internal process of elaboration and acquisition. Therefore, the learning content is, so to speak, always ‘obsessed’ with the incentives at stake — e.g. whether the learning is driven by desire, interest, necessity or compulsion. Correspondingly, the incentives are always influenced by the content, e.g. new information can change the incentive condition.
The idea of ‘obsession’ here will become vivid if you have ever worked with learners who seemed to be overly driven by some goal outwith your intentions — for example a test, a job interview, or the current task at hand. Information they see to be irrelevant simply washes over them, while whatever is immediately applicable they will persistently enquire about.
Unless, that is, you find a way to convince them that a particular topic really is relevant to their ultimate goal. In this way, interaction influences content, which then influences incentive, itself influencing interaction to drive more productive engagement, and therefore influencing content once more.
Thus the triangle depicts what may be described as the tension field of learning in general, and of any specific learning event or learning process as stretched out between the development of functionality, sensibility and sociality.
This image of learning events being ‘stretched out’ over the triangle is instructive. Every learning event involves all three dimensions, and isn’t at an individual spot on a triangular map.
Illeris adds a final note:
It is also important to mention that each dimension includes a mental as well as a bodily side. Actually, learning begins with the body and takes place through the brain, which is also part of the body, and only gradually is the mental side separated out as a specific but never independent area or function.
This can be easy to forget, especially for us in technology where our work is often cognitively biased. To illustrate this, imagine debugging a tough interview problem in a hot cramped room. The incentive dimension can quickly lose balance under assault both from demanding content and a high-pressure environment. Recovery becomes hard as the body begins to sweat and the voice shakes, further deteriorating the incentive dimension and compromising the person’s ability to manage mental effort towards the content. The thought of losing the opportunity arises, and the learner begins to shift energy away from the problem and towards finding a way to recover or escape.
A visual analysis tool
Illeris’ Three Dimensions are a useful tool, but the visualisation provides an opportunity for improvement. I’ve drawn on Rich Picture diagrams from systems thinking to create the below.
You may wish to zoom in!
This diagram maps out a learning situation. The scenario is of an apprentice driver learning the emergency stop procedure. The three dimensions are used as a space to plot complex interactions between incentive, content, and interaction. It’s an interesting way to represent it, and we can clearly observe the tension between the learner’s anxiety, the instructor managing the environment, and the cognitive limits of the learner.
As an analysis tool this shows promise. One problem I’ve not managed to solve yet is that a triangle doesn’t have that much space in it relative to the space it takes up on the screen! As such, the diagram tends to ‘spiral in’ and run out of room.
Interestingly, I found it necessary to create a ‘linking space’ between incentive and content to cover the learner actually responding to incentive by directing cognitive effort towards particular things.
I’ve created a template on Miro that you can use here.
What does this mean for tech education?
I have had the privilege of working with school teachers and observing some of their work. One thing that always strikes me is how much attention they pay to Incentive.
It’s not a big surprise — school systematically incentively challenged. The learners have at best a theoretical idea of what the demands and rewards of the post-school world are like. Many children understandably react to the pressure of school-era incentives by questioning their importance.
Competing with this are the highly compelling rewards of their peer society. I was fairly studious, but even I couldn’t resist the exhilaration of being in a lively class with a propensity to turning against the teacher.
As such, school teaching requires a heavy investment in incentive, purely because they are competing against very powerful forces. They must gain the attention and interest of their learners, build rapport, praise, direct, and overall maintain a lively but focused atmosphere. When teachers speak of ‘losing the class’ it is primarily the incentive dimension that has spiralled out of control.
Incentive is at play in adult tech education settings too — but it is quite different. Analysing incentive can be a powerful tool for understanding our learners better and building a better relationship with them.
Apprentice developers are often more aware of the demands of work and the rewards that a career in tech can offer. As such, they can be very motivated towards achieving their goals. This gives rise to a few archetypes:2
The Maker Developer. This learner loves building things. They often speak of building websites or apps and serving users. They sometimes (but not always) gravitate towards frontend work.
Their incentive complex is boosted by seeing that they have created useful products, often showing visual appeal.
It can be challenged by a lack of investment in technical detail (content) leading to being unable to achieve their vision (interaction), becoming discouraged, thereby further damaging their learning.
This can be addressed by regular technical mentorship and gently pushing fundamentals as a way to achieve the flair they desire.
The Mastery Developer. This learner loves writing code. They wrestle with technical concepts and detail primarily and don’t care much about building fleshed-out products or visual appeal. They sometimes (but not always) gravitate towards backend work.
Their incentive complex is boosted by solving challenging coding problems and mastering new concepts.
It can be challenged by a lack of investment in software quality (content) and overvaluing ‘clever’ solutions (incentive), leading to poor results in a job search or professionally (interaction), becoming discouraged, and often then investing further in challenging technical concepts rather than in quality (incentive). Some have given up, becoming incredulous that the technical bar could be so high — missing the point about quality.
This can be addressed by explaining in an organisation software is built by a team. If their code makes the team slower it will harm the progress of the project. If their code makes the team faster it will help. So when interviewing it is important to show that you can write code that will be easy for the team to work with — tests, clear naming, effective structure.
(Or, ship them off to somewhere that really only values technical aptitude!)
The Professional Developer. This learner wants to build a career. They aren’t hugely passionate about product success or technical detail, but they do know that tech is a good place to work and they want to have a good job. There’s nothing wrong with this!
Their incentive complex is boosted by gaining a clear understanding of what they need to do to get a job, having a plan, and making progress towards that goal. They often keep track of industry trends and care about best practice.
It can be challenged by a certain narrow-mindedness when it comes to deepening their knowledge, or by uncertainty on behalf of their career guides. They’re mission-driven and, like all of us, when our mission is instrumental we try to find the easiest route. If you give them work they see as irrelevant they will become frustrated and, if you are lucky, challenge you on it.
This can be addressed by regularly reinforcing the intention behind the skills being taught and grounding it in their ultimate professional goal rather than appealing to their sense of technical passion. This involves knowing the purpose of the learning yourself too — if it is just a side-quest, be honest with them and let them choose.
And if they gain some passion along the way — more credit to you!
Notes & credits
Photo by Vidar Nordli-Mathisen on Unsplash
Knud Illeris, A Comprehensive Understanding of Human Learning, found in the book Contemporary Theories of Learning (2018), pages 3-5. ↩︎
With thanks to Sam Morgan for these archetypes shared in conversation, which I am merely paraphrasing here. ↩︎
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