The 6 Levels of Educational Complexity and How to Use Them
The abstract concepts of educational psychology can be surprisingly useful for students.
There have been many different attempts to classify students’ levels of understanding in order of difficulty by different educational psychologists. These range from Bloom’s Taxonomy of Thinking Skills, to the DIKW pyramid, to the somewhat daunting 16 tiers of Michael Commons’ Model of Hierarchical Complexity. If getting to grips with all of these different ways of classifying understanding sounds a bit too much like hard work, it’s reassuring to note that they agree more often than they differ from one another, so there are generalisations that can be made between them.
But why is this useful? Where an understanding of the different levels of educational complexity is invaluable is those occasions where your teacher is asking you to step up in some fashion, but you’re not entirely sure what it is that you’re not doing yet. For instance, you might have had feedback saying that your essay contains too much explanation, and not enough analysis. Or you might be getting lower marks than a friend whose understanding of the topic seems to be on a par with yours. Chances are, what you need to do is step up to the next level of educational complexity.
It is worth noting that many of these different models and taxonomies have been criticised in various ways, usually because they are too rigid or prescriptive, or the ways in which they have been used in an educational context go beyond those for which they were intended. In this article, we’re going to suggest a few ways that you can use these models, but do remember that they aren’t meant to be taken as fixed and absolute, just used as most benefits your own learning.
Bearing that in mind, here’s our guide to levels of educational complexity, and how you can use them in your learning:
1. Remembering and repeating
The most basic level of educational complexity – agreed on by almost all theorists – is the level of remembering and repeating. This is something that can be done by computers, humans and any animal that can be trained. For instance, domesticated rabbits can be house-trained; they are able to remember that they have been encouraged to use a litterbox, and then they can repeat this action. It doesn’t mean that they understand what a carpet is, or why you might prefer to keep it clean.
This is the level of complexity that you can achieve by rote learning. You can recite that one times three is three, two times three is six, three times three is nine and so on, without necessarily having any understanding of number theory, or being able to work out that three times four is twelve. With times tables in particular, it’s easy enough to spot when they have been learned by rote without understanding – it’s when someone can repeat that three times six is eighteen, but can’t work out that this means six times three will come to the same number.
Despite this being the most basic level of complexity, rote learning isn’t something to be sniffed at. For instance, in maths and science, there may be formulae that you want to be able to memorise in case you need them, but the hard work of puzzling them out is something you’re prepared to save until it becomes essential.
Being able to learn by rote can save you in subjects that you struggle with, as well. For instance, you might not be able to get your head around Middle English enough to know what Chaucer is on about when he says that “the yonge sonne/ Hath in the Ram his halve cours yronne” in the General Prologue to the Canterbury Tales, but if you can recite it as evidence that the tales are set in the spring, it might be enough to get you through an exam question even if you don’t understand it. (For reference, ‘the Ram’ refers to the constellation of Taurus, and the sun being in Taurus indicates the time of year).
2. Understanding information
When you remember and repeat, you deal with data – text and numbers that are meaningless without context applied. When you understand something, you deal with information, which is data with a context. To use the rabbit example, the rabbit doesn’t understand why it isn’t allowed to pee on the carpet, it just does as it’s been told. You, as a human, do understand why, and could probably list several reasons. Being able to remember and repeat is a commonplace skill; being able to understand is restricted to a far more limited range of species.
Demonstrating understanding is usually quite straightforward. For instance, if you can explain something in your own words, then that indicates that you have understood it, rather than simply repeating it. Different educational systems approach this differently; while some will prefer you to demonstrate understanding by phrasing things differently from how your teachers or textbooks did, others will prefer you to use a given phrasing. However, for your own understanding, you should be able to paraphrase at will, even if that isn’t the version you’re encouraged to write in exams.
Although understanding is still a relatively low-level educational skill, it’s at this level that many students become stuck. An answer based on understanding is what you might instinctively give when a task says something like “explain why”, such as “explain why castles have high walls”. You might say that castles were defensive buildings, and high walls are harder for attackers to climb than low walls. This is the kind of answer that computers can be programmed to give – but you’ll see that there are many additional levels of complexity to come.
3. Applying knowledge
Some models go straight from understanding to analysis, but another level that can be helpful to include in between the two is application. Applying knowledge means taking the knowledge you have gained in one place and using it in another. Once you start applying knowledge, you can learn through deduction and create syllogisms. A syllogism is a statement where you draw a conclusion from two premises – so, to take our castle example, you could say high walls were useful for defence in medieval times; castles have high walls; therefore castles were useful for defence.
But in that syllogism, you were only working with the information you already had from the ‘understanding’ level. Knowledge is information that can be applied in other circumstances. So you might apply your knowledge about castles and high walls to thinking about watchtowers, and noting that they too have high walls – therefore, they, too, are useful for defence.
You might at this point be thinking of other medieval buildings with high walls that were not intended for defence (or much use for it), such as cathedrals. If so, great. If you have the information that cathedrals have high walls but were not defensive buildings, you can apply that and gain the knowledge that medieval buildings could have high walls for all kinds of different reasons. When put so bluntly, this might seem obvious, but students who are stuck at the ‘understanding information’ level might just pick on the first explanation that they can think of, without applying other information to work out if it’s the right explanation or not.
4. Analysing knowledge
This is the level that you will be expected to start operating at from secondary school onwards. Trying to work out the difference between understanding and applying knowledge, and analysing it – and how to level up from one to the other – has given many students a headache. We’ll try to clarify it here.
Let’s go back to the question about the castle – “explain why castles have high walls”. At the level where you both understand and apply knowledge, you might say that castles have high walls because high walls are a status symbol that will impress peasants; because they enable soldiers to look out for approaching danger; because they enable those same soldiers to defend against enemies. You might know that cathedrals have high walls to glorify God, but that this isn’t relevant for non-religious buildings like castles, so you don’t include it. And you might think that’s a pretty thorough answer, job done.
But there isn’t any analysis in the above answer. When you are analysing, you ask why. Why are high walls a status symbol? Why does it matter if the peasants are impressed or not? Why do soldiers need high walls for defence, rather than just a big hill, or other fortifications? Why are high walls useful for medieval defences, but less so in later centuries? Why are there enemies against which the castle needs to be defended? Why are walls the particular height that they are, and not a lot higher or a lot lower? With analysis, the amount of depth that your answer could go into is nearly endless. You can see a book – or a series of books – deriving solely from what seemed like a basic question about castle walls.
5. Applying wisdom
At the upper reaches of the levels of educational complexity, the models start to diverge. Some put analysis and evaluation on the same level, or add in other concepts, such as creativity. Furthermore, the definitions of concepts start to become a little fuzzier, such as the difference between ‘knowledge’ and ‘wisdom’, which forms the basis of the next level that we’ve identified. You might well have heard the quote – misattributed to a variety of different people – that “knowledge is knowing that a tomato is a fruit. Wisdom is not putting it in a fruit salad.” It’s witty, but it’s hard to know exactly how to apply it if you’re writing an essay.
One way of looking at this is that it’s about relevance. You know that a tomato is a fruit, but that knowledge is irrelevant in a fruit salad context, where what you actually want is sweet fruit that might go nicely with some cream. Going back to the castle example, the questions that you came up with for your analysis would fill several books – so applying wisdom involves knowing which ones to answer in a 10-mark question and which ones to discard. It’s knowing that your answer probably shouldn’t begin with the origin of agriculture, even though you can follow a thread of analysis that leads you directly to the height of castle walls.
Exam technique belongs in this category, as well as how you present your knowledge more generally: being succinct, or using persuasive techniques, for instance. It’s also about being able to assess reliability in the sources you encounter. You can see how the categories begin to overlap; you might be able to present information in a persuasive manner at a stage before you can analyse it, for instance.
6. Evaluating in the abstract
The highest-level skill, which some people don’t develop until they reach university, is being able to evaluate everything you have learned on an abstract level. Going back to castle walls, it’s the ability to read Medieval Fortifications and Their Extended Purposes and Castles: A Military History, compare the points of view expressed by the two authors, assess which one, if either, you believe to be correct, and come to form your own opinion.
In order to do this, you need to be able to understand, apply knowledge, analyse and assess relevance, as well as looking at the bigger picture, come to your own conclusions, and defend your own opinion. In other words, you need to have a command of all of the other levels of thinking skills in order to be able to evaluate in the abstract; you can’t jump ahead through the levels. You also need a good deal of data, information and knowledge to begin with, or your evaluation will have no foundations, regardless of your level of critical thinking skill.
You can assess whether you’ve mastered the skill of evaluating in the abstract by seeing if you can defend perspectives other than your own, or if you can transfer your analysis from one domain to another – for instance, can you take your understanding of medieval castle defences in the UK, and use them to analyse Aztec defensive structures? Can you see the points where it might be applicable, and the points where it would fall down? If so, well done – you’ve figured out how to evaluate a topic in the abstract, and by implication, the other levels of thinking skills as well.
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