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How memory works is actually how curriculum should work

Written by: Juan Fernandez
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6 min read

How we learn

It’s been more than 100 years since Edward Thorndike published his book Educational Psychology (1913), establishing the foundations of the science with that name. A few years earlier, his master, William James, had described a model with two types of memory: primary and secondary. According to this model, the primary memory consisted of thoughts that were consciously held for a short time, while the secondary memory consisted of a permanent, unconscious storage of data (James, 1975). Thanks to Thorndike and James, in 1968 Atkinson and Shiffrin developed a model proposing that human memory is made up of three parts: a sensory register, where sensory-type information becomes part of memory; a long-term data storage, where memories, facts and procedures are stored; and a short-term data storage, also called working memory, which receives sensory data as well as data from long-term memory.

During recent decades, alternative frameworks have emerged from this model, with Baddeley and Hitch’s model (Baddeley and Hitch, 1974; Baddeley et al., 2020) the most accepted and the most important for teachers to understand. The central idea is that when we are doing a task, we use a specific type of memory (working memory). In working memory, there is a regulation system that decides which data that we have just obtained must be stored temporarily, because it will be useful to us while the task is being carried out. It also decides which data must be retrieved from knowledge that we have already acquired long ago (long-term memory), because it will also be useful to us in relation to the task that we are doing.

There are many huge implications of this model – for example, cognitive load theory (Sweller et al., 2011) or the dual coding hypothesis (Paivio, 2014). The importance of these theoretical advances is parallel to a huge interest in how to apply them in the classroom. For this reason, we can find dozens of books whose titles include (totally or partially) ‘how we learn’ – a quick search of Google Books garners hundreds of results.

Intriguingly, scientific research about curriculum has not gone the same way. It seems that ‘how we learn’ has been developed independently from ‘what to learn’. If cognitive science has proven a fruitful discipline to understand how we learn, it might also be a good resource to think about curriculum design.

What to learn

Generally, we understand the school year as a succession of lessons, or units, that are assigned a number of hours in the initial planning. In each one of these we work on different ideas: concepts, procedures, etc. If we ask teachers to summarise the curriculum to be taught in one course, we will maybe come up with a list of ideas. We could represent these ideas as black dots (Figure 1).

This system has several major advantages: it is simple, easily exportable from one course to another and from one teacher to another, and allows us to just follow the teaching guide and get on with it. However, over the years, I have become aware of its serious limitations. One of these is that not all ideas (concepts or procedures) are equally important. In fact, there are some key ideas without which it is impossible to acquire the others.

If the current model of memory considers previous knowledge and the past experiences so highly, one good question when designing the curriculum should be: ‘How many connections can be made with that idea?’ The existence of ‘big/key ideas’ (Figure 2) has been developed for science education – for example in Principles and Big Ideas of Science Education (Harlen and Bell, 2010). The aim here is to identify those ideas that are essential for a deep understanding of the topic in general or even the whole subject. If I were asked for key ideas for biology, for example, I would choose cell function and structure. This is the kind of concept that I need to master in order to develop a good understanding of mitosis, microorganisms and organs, for example. Thus, when new things come up, they can be connected with a solid understanding of the key ideas.

Following Mary Myatt (2020), I believe in the need to renew the school curriculum by trying to prioritise quality over quantity – in other words, covering less in order to be able to go deeper. Some may think that these key ideas (the major points) correspond to the minimum content. From my point of view, this is not always the case. Let’s remember that the width of the dot represents how important this idea is for understanding other ideas. For example, to understand the Renaissance you need to have a good understanding of some features of the Middle Ages, or to use the second conditional in English, you need to know how to use the simple past. This relational aspect between the parts of the school curriculum is the first thing that should be considered in a reform of the curriculum. The curriculum is not a list, but a network (Figure 3).

In Figure 3, the colours represent related ideas between different courses. Of course, this model could also be used for other subjects. If you look again at Figure 1, a traditional view of the school curriculum takes into account neither the hierarchy nor the network of relationships between these key ideas. The advantage of looking at the school curriculum in this way is that, especially in online teaching, the relationships between ideas can be a very powerful tool. I propose that mapping in this way would help students to see what they are learning in an overall framework as a ‘pathway of ideas’.

This way of viewing the curriculum mimics the regulation system of the working memory, which decides which knowledge is relevant and must be stored temporarily, because it will be useful to us in the future. The network also makes it explicit which knowledge must be retrieved from what we have already acquired long ago (in other courses). This might be helpful for teachers, as they could start with a small retrieval practice session that focuses on those past concepts that will be important for the current lesson.

An example using my subject of biology can be seen in Figure 4. A protozoan or a bacterium can provide the best example of what a cell is (eukaryotic or prokaryotic, respectively) and at the same time help us to better understand an unseen part of biodiversity.

The example chosen is not accidental. In my experience, many students finish compulsory education without clearly distinguishing what a cell is, despite the fact that it is a concept that has been studied since the start of secondary school.

The importance of these maps is that they allow students (and teachers) to remember which are the key points to understand and how they relate to each other. In this sense, as a ‘pathway of ideas’, it also represents in some way the mental process of understanding the curriculum in depth, and provides useful clues for formative assessment and feedback to students.

Normally we will do this walkthrough with students in class, going back to review what is important to understand what we are working on now. With e-learning, it is more complicated. The danger is that we turn online teaching into a series of disjointed tasks, like a succession of PDF activities. We can understand the meaning and sequence of the activities, but we should not assume that our students will understand this relationship.

On the other hand, this proposal has several constraints related to educational laws. Teachers must adapt to the prescribed sequence of a national curriculum and exam syllabus where they exist. Depending on the level of concreteness, this will require more time and effort.

Finally, feedback from other teachers has pointed out that this planning can be very useful for projects. Relationships between ideas from different subjects that we may take for granted may not be the case for students. In this way we all work on the same map: we make it explicit and present it. We can go through it and revise it together.

References
  • Atkinson RC and Shiffrin RM (1968) Human memory: A proposed system and its control processes. Psychology of Learning and Motivation 2: 89–195.
  • Baddeley A, Eysenck MW and Anderson MC (2020) Memory, 3rd ed. London and New York: Routledge.
  • Baddeley AD and Hitch G (1974) Working memory. Psychology of Learning and Motivation 8: 47–89.
  • Harlen W and Bell D (2010) Principles and Big Ideas of Science Education. Hatfield: Association for Science Education.
  • James W (1975) Works of William James. Cambridge, Mass: Harvard University Press.
  • Myatt M (2020) The Curriculum: Gallimaufry to Coherence. Woodbridge: John Catt.
  • Paivio A (2014) Mind and Its Evolution: A Dual Coding Theoretical Approach. Hoboken: Taylor and Francis.
  • Sweller J, Ayres P and Kalyuga S (2011) Cognitive Load Theory. New York: Springer New York.
  • Thorndike EL (1913) Educational Psychology. New York: Teachers College, Columbia University.
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