What do you want your pupils’ memories to be like?
Perhaps your wish list looks like mine:
- Contain important subject knowledge (not irrelevant contextual details, e.g., the bee that flew into the classroom!).
- Allow for flexible thinking.
- No misconceptions.
Let’s find out how memories form in the brain and how teachers can help pupils create ideal memories that fulfil our wish list.
Ideal memory is generalised
Generalised memory means memories not tied to a particular event.
Knowledge of facts, ideas and concepts are generalised because they can be used across situations (Badre & Wagner, 2002). They help us think more flexibly and carry out important skills (Schlichting & Preston, 2015).
To understand why generalised memory is helpful, here’s a fictional scenario:
Pupil 1 was taught to calculate perimeter and tackled lots of different questions: they have a rich understanding that ‘perimeter is the distance around a 2D shape’.
Armed with this general rule, when asked a question about calculating ‘the perimeter’, they accurately predict they must calculate the distance around the shape/football pitch/garden etc.
Pupil 2 remembers individual events:
‘Yesterday, period 2, in maths, I calculated the distance around a football pitch and this was ‘the perimeter’’.
‘Last week, Tuesday, I sat with Zainab and calculated the distance around a triangle.’
Pupil 2 has individual memories of perimeter tied to the lesson event. They have retained all the contextual details (related to time and place).
Faced with another question about perimeter, Pupil 2 is stuck: they don’t have a generalised rule. They think perimeter relates only to triangles and football pitches!
Pupil 1 has the edge. By abstracting away from specific events, they’ve formed generalised memories they can use to tackle different questions, i.e., apply knowledge more flexibly.
Takeaway: generalised knowledge = more flexible thinking.
Luckily our brains are on our side. The brain creates generalised memories because these enable it to make better predictions in new situations, just like Pupil 1 does (Kroes & Fernández, 2012).
Let’s see how the brain creates generalisations.
Storing memories creates generalisations
Imagine the three shapes below each represent a memory for an event where you learned about ‘perimeter’. These memories are called ‘episodic memories’. They contain unique contextual details of where/when an experience happened (Tulving, 2002).
The brain identifies commonalities across these events (red dots) and integrates them into a network of related memories (red-dot network below).*
This network is called a ‘schema’ (Gilboa & Marlatte, 2017) and the process of integration into the schema is called ‘consolidation’ (Squire et al., 2015).
The red dot schema represents our generalised knowledge, e.g., what perimeter means/steps to calculate it/details of common examples. Generalised knowledge is called ‘semantic memory’.
The contextual/episodic details of time and place (dots that are not red) can’t enter the schema because they are unique and don’t fit within a network of related knowledge.
This means some contextual details become almost impossible to access. Others (the ‘gist’ of the event) may be loosely connected to the network (dashed lines) (Miyashita, 2004) and recalled only if specific cue are used (Sekeres et al., 2018).**
What sticks in memory is the generalised knowledge that’s entered the network: our semantic memory.
Takeaway: storing memories changes them from contextually-detailed episodes to semantic generalisations (facts, concepts and ideas) people can use across situations to think more flexibly.***
This is good news! The brain seems to be working to create the generalised memories teachers want.
The facts, concepts and ideas we want pupils to learn (algebra, totalitarianism, anaerobic respiration etc.) are really hard.
What can teachers do to support pupils to form these generalisations?
(1) Use examples to create rich generalisations
Teachers teach facts, concepts and ideas (generalisations) in meaningful ways using examples/analogies/illustrations/questions etc.
Take examples. Examples should convey the concept to its fullest so pupils can create a rich generalisation.
Imagine teaching pupils what a ‘euphemism’ is. You’d want to select a range of examples, e.g., euphemisms used to be polite, to deceive, to mask unpleasant truths etc., whilst highlighting the common ingredients of a euphemism across the examples. (Depending on the learners, teachers may not introduce these examples all at once).
This helps pupils create a rich generalisation.
Relatedly, the details of the examples/analogies/illustrations/questions need to vary (Pashler et al., 2007).
Imagine a pupil who learned about osmosis through examples of potato slices in saltwater. Their generalised knowledge of ‘osmosis’ is tied to potato slices. When they are asked about osmosis in a different context (even with a different vegetable) they are stumped!
To avoid this, teachers can vary the details they do not want pupils to generalise.
(2) Keep memories sufficiently detailed
Memory that is overgeneralised can lead to misconceptions. By overgeneralised we mean memories that do not have enough connections to other knowledge and have lost too much episodic detail.
Here’s an example:
Sunlight is vital for plant photosynthesis. It’s also crucial to human survival too but in a different way. A pupil with overgeneralised knowledge knows ‘the sun is important’. This overgeneralisation leads to the misconception ‘the sun plays the same role for humans and plants’.
The pupil has formed a misconception based on a lack of detailed knowledge (van Kesteren & Meeter, 2020). They need memory that is sufficiently detailed to distinguish the sun’s roles in plant vs. animal life.
Teachers can preserve sufficient detail through –
Elaboration: this is where pupils make lots of connections between the to-be-learned information and what they already know (Hamilton, 2012). For example, pupils link what they know to numerous examples.
Varying retrieval-practice (low-stakes test) questions. Retrieving bare facts strips memory of detail. Instead, vary the types of questions so pupils have to ‘come at’ knowledge in different ways, e.g. –
‘Name the key elements of photosynthesis.’
‘What role does sunlight play in the lives of a) plants and b) animals?’
(3) Be alert to misconceptions
Imagine a pupil has the misconception that when living things grow, their cells enlarge (rather than multiply). They carry a similar misconception into another topic and assume when liquids/gases expand, their particles (rather than the space between them) get bigger.
A network of generalised knowledge that amounts to a misconception is hard to change and keeps rearing its head across topics.
Some misconceptions may never be dispelled. However, there’s evidence from a study about learning counterintuitive concepts that pupils can be supported to inhibit misconceptions by asking them to ‘stop and think’ (Roy et al., 2019). This gives them a chance to activate the knowledge they have been taught that overrides the misconception.
So now we know ideal memories for pupils are generalised and sufficiently detailed. In the next blog we find out how our brains store memories. This provides teachers with fundamental insights about the learning process!
*Note, the brain doesn’t just extract commonalities in a statistical way. It prioritises storage of certain memories, e.g., emotive memories (de Voogd et al., 2016). However, I wouldn’t recommend trying to make learning emotive. Aside from this being difficult, I can see it backfiring for pupils.
**Giving pupils contextual cues, e.g. ‘We discussed this just after I modelled the steps to you”, can help trigger memory for semantic knowledge.
***Some memories may get fast access to schemas i.e. we can learn them faster. We look at this in a future blog!
Badre, D., & Wagner, A. D. (2002). Semantic retrieval, mnemonic control, and prefrontal cortex. Behavioral and cognitive neuroscience reviews, 1(3), 206-218.
de Voogd, L. D., Fernández, G., & Hermans, E. J. (2016). Awake reactivation of emotional memory traces through hippocampal–neocortical interactions. Neuroimage, 134, 563-572.
Gilboa, A., & Marlatte, H. (2017). Neurobiology of schemas and schema-mediated memory. Trends in cognitive sciences, 21(8), 618-631.
Hamilton, R. (2012). Elaboration Effects on Learning. Encyclopedia of the Sciences of Learning, 3, 1103-1105.
Kroes, M. C., & Fernández, G. (2012). Dynamic neural systems enable adaptive, flexible memories. Neuroscience & Biobehavioral Reviews, 36(7), 1646-1666.
Miyashita, Y. (2004). Cognitive memory: cellular and network machineries and their top-down control. Science, 306(5695), 435-440.
Pashler, H., Bain, P. M., Bottge, B. A., Graesser, A., Koedinger, K., McDaniel, M., & Metcalfe, J. (2007). Organizing Instruction and Study to Improve Student Learning. IES Practice Guide. NCER 2007-2004. National Center for Education Research.
Roy, P., Rutt, S., Easton, C., Sims, D., Bradshaw, S., & McNamara, S. (2019). Stop and Think: Learning counterintuitive concepts. Evaluation report and executive summary. Education Endowment Foundation.
Sekeres, M. J., Winocur, G., & Moscovitch, M. (2018). The hippocampus and related neocortical structures in memory transformation. Neuroscience letters, 680, 39-53.
Schlichting, M. L., & Preston, A. R. (2015). Memory integration: neural mechanisms and implications for behavior. Current opinion in behavioral sciences, 1, 1-8.
Squire, L. R., Genzel, L., Wixted, J. T., & Morris, R. G. (2015). Memory consolidation. Cold Spring Harbor perspectives in biology, 7(8), a021766.
Tulving, E. (2002). Episodic memory: From mind to brain. Annual review of psychology, 53(1), 1-25.
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