Tag Archives: psychology

What did memory evolve to do?⤴

from @ Memory & Education Blog - Jonathan Firth

It is thought that most of human evolution took place on a grasslands environment, but how does that affect learning and memory today? Image by Diana Robinson. 

It is thought that most of human evolution took place on a grasslands environment, but how does that affect learning and memory today? Image by Diana Robinson

Humans have evolved over the course of millions of years. Since we last shared a common ancestors with chimpanzees more than 6 million years ago (White et al, 2009), a number of hominin species have evolved - most, of course, have died out (as recently as 100,000 years ago, 4-5 homo species existed concurrently).

For most of this time, our ancestors and near relatives probably lived in grasslands environments, hunting and gathering. This environment has shaped our physical bodies as well as our behaviour - from our appetite for fatty and sweet foods, to our large brains which facilitate cooperation and interactions in large tribes.

Role of evolution in memory

Beyond a general acknowledgement that our brains and cognitive abilities are the product of evolution, human memory research has largely ignored our evolutionary history, focusing on short-term processing (see Bahrick, 2005) and using tasks which take little account of the context in which things are encountered in the real world.

An important advance was made when James Nairne and colleagues conducted an experiment demonstrating that people remember information better when they process it in a grasslands scenario. In an ingenious study, participants were shown a list of words such as truck, juice, chair and sword and were then asked to rate how relevant these objects were to the following scenario:

Remarkably, in a later surprise test, participants remembered the words significantly better having thought about them in this context compared to the other conditions used in the experiment - one of which involved a moving house scenario, and the other required participants simply to think about the pleasantness of the word (a standard memory intervention which promotes deep processing).

If this sounds like a fluke, the effect has been replicated several times and by many different researchers; other comparison scenarios have been tried - for example a bank robbery (Kang et al, 2008), zombies in the city (Soderstrom & McCabe, 2011), and even an 'in the afterlife' scenario (Röer et al, 2013) - but none have proved superior or even equal in promoting recall of a set of items.

Is this truly 'survival processing'?

A simple but very general question arises from this work - assuming that our evolution has prepared us to do certain things better than others, how specific are these abilities? Have we really been hard-wired to process grasslands survival situations better than other situations in a way that affects all of human memory today?

Alternatively, is the grasslands research scenario somehow drawing on a more general aspect of memory that the other scenarios fail to tap into?

My reading of the research literature so far gives the impression that many researchers are trying their best to demonstrate the latter. Three particularly interesting possibilities include:

- It causes us to plan more more than other scenarios, and planning leads to better encoding to memory (Klein, 2014).

- It causes us to encode items more richly (Bell et al, 2015). Elaborative encoding is well known to benefit long-memory - which, after all, is based on making meaningful connections.

- It allows for more creative thinking in terms of how the objects are used. In keeping with this possibility, Wilson (2016) found that a grasslands scenario was also better at promoting creative thinking about object uses than any of the other widely used comparison conditions. If we think creatively about something, we may well remember it better due to the generation effect.

The exact variables at play are still under investigation, and it could be a combination of these factors - the grasslands scenario may promote more creative, future-focused and meaningful thought processes. It is curious, however, how no other scenario has so far proved to be comparably successful in boosting memory - at least with the original tasks and materials.

What does this mean for education?

As a relatively new area of research, survival processing has not yet had a significant impact on education, but it does have potential. With further testing, a set of principles could be established, allowing classroom activities to be designed to incorporate elements of risk/danger, future planning, creativity, etc.

Survival processing is not the only possible effect of evolution on memory that could impact on education. For example, we also remember animals better than inanimate objects - an effect which has been trialled for use in the learning of language vocabulary (Nairne, 2016).

More broadly, many of the most robust findings from the study of memory make perfect sense from an evolutionary perspective. The spacing effect, for example, fits with the idea that any animal needs to deal with a one-off problem, but needn't waste mental resources storing the responses long-term. In contrast, if something happens periodically with time gaps in between - a type of food that grows seasonally, migrating predators or occasional floods, for example - the adaptive response is to create a more lasting mental record of any any relevant details as well as successful responses that we have previously used.

Similarly, the perspective that students learn better if tasks connect to their interests and social context makes a lot of sense from a survival point of view (at least for social species such as our own), as does the idea that interleaving our learning - something that would happen a lot in the natural world - is advantageous in the 'inductive learning' of patterns and rules.

The classic Zeigarnik effect - incomplete tasks being better remembered than complete ones - also fits well with a scenario where an unfinished task could be a matter of life or death.

Clearly, we can't deliver entire school courses via a grasslands scenario like the one described above. We could, however, pay more attention to the ways in which memory has evolved to work, and establish ways of building these principles into classroom tasks.


Bahrick, H. P. (2005). The long-term neglect of long-term memory: Reasons and remedies. In A.F. Healy (Ed.), Experimental Cognitive Psychology and its Applications. Washington, DC: American Psychological Association.

Bell, R., Röer, J.P. & Buchner, A. (2015) Adaptive Memory: Thinking about function. Journal of Experimental Psychology: Learning, Memory & Cognition, 41, 1038 – 1048 http://dx.doi.org/10.1037/xlm0000066

Kang, S. H., McDermott, K. B., & Cohen, S. M. (2008). The mnemonic advantage of processing fitness-relevant information. Memory & Cognition, 36(6), 1151-1156.

Klein, S.B. (2014). Evolution, memory and the role of self-referrant recall in planning for the future. In B.L. Schwarz, M.L. Howe, M.P. Toglia and H. Otgaar (Eds.) What is Adaptive about Adaptive Memory? pp. 11-34. Oxford: OUP.

Nairne, J. S. (2016). Adaptive Memory: Fitness-Relevant “Tunings” Help Drive Learning and Remembering. In D.C. Geary & D.B. Berch (Eds), Evolutionary Perspectives on Child Development and Education (pp. 251-269). New York: Springer.

Nairne, J. S., Thompson, S. R., & Pandeirada, J. N. (2007). Adaptive memory: survival processing enhances retention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(2), 263.

Röer, J. P., Bell, R., & Buchner, A. (2013). Is the survival-processing memory advantage due to richness of encoding?. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39(4), 1294.

Soderstrom, N. C., & McCabe, D. P. (2011). Are survival processing memory advantages based on ancestral priorities?. Psychonomic Bulletin & Review, 18(3), 564-569.

White, T. D., Asfaw, B., Beyene, Y., Haile-Selassie, Y., Lovejoy, C. O., Suwa, G., & WoldeGabriel, G. (2009). Ardipithecus ramidus and the paleobiology of early hominids. Science, 326(5949), 64-86.

Wilson, S. (2016). Divergent thinking in the grasslands: thinking about object function in the context of a grassland survival scenario elicits more alternate uses than control scenarios. Journal of Cognitive Psychology, 1-13.

Memory in education – a mission statement⤴

from @ Memory & Education Blog - Jonathan Firth

Most students take notes during lessons, but are they adding information to memory? Image by Nick Olejniczak

Most students take notes during lessons, but are they adding information to memory? Image by Nick Olejniczak

I believe that memory is very important in education. This might seem obvious - of course children and students need to remember things. Perhaps it also seems threatening - reducing education to mere passive memorisation?

I don’t think so.

In my view, improving how we use memory is not threatening because remembering is essential regardless of your view of how teaching should be done, or what the syllabus should consist of. Whether you are talking about lectures or discovery learning, a minimum requirement is that the pupils retain some of the information that you have been teaching, and develop skills and understanding over the long-term.

Indeed, educational approaches tend to be judged, at least in part, according to whether people remember anything in terms of their performance on tasks (real or artificial) or tests at a later date. As a learner, a class might be a lot of fun, but I would ask myself whether it was a worthwhile use of my time if I later couldn’t remember anything about it.

From a psychology or neuroscience perspective, we are talking about encoding facts, skills and schema knowledge that is retained over the long-term. This learning is represented in the physical brain by changes to neural structure. There is no learning without these things happening!

Perhaps memory can seem to be a threat because it appears reductive - breaking education down to a list of testable facts. But actually, this may just be a matter of definition; cognitive psychology takes a broader view of memory than that used in everyday speech, and includes any change in behaviour or thinking. This could include developing our creative skills, for example, or our ability to write an essay. There are, of course, various different types of memory - memory for a fact, an experience, a task, and so on. But all of them require, on some level, that the learner takes something in, and that it persists for long enough to affect their future actions and/or thoughts.

I would agree that too much of what currently passes for education is founded on shallow memorisation - much of what is crammed for exams is swiftly forgotten, particularly if not well understood to begin with. But this is exactly where research can come in - by telling us how to make learning last.

As for the role of memory being obvious, well… Perhaps something so fundamental should be seen as obvious, but as such it is easily ignored and neglected. I’d argue that the role of memory is not prominent in current educational debates, and plays too small a role (if any) in teacher training and CPD.

When we talk about improving education, we are essentially saying that we want pupils to do better at maths, science, languages, social science etc, in a way that will allow them to:

  1. pass exams
  2. retain skills that they can use in future

This means that they need to retain key facts (such as what hydrogen is) and skills (such as how to multiply two fractions) for long enough not just to pass an assessment, but also to use it an unspecified period of time in the future - i.e. it must be retained in long-term memory, and be amenable to transfer.

The newly re-elected Scottish Government has made it very clear that education is a top political priority, and First Minister Nicola Sturgeon has highlighted that we must try to ‘close the attainment gap’ in terms of the academic under-peformance of the least well-off young people in our society. I would certainly commend that sentiment. I would also suggest that interventions that have been shown to improve attainment exist in the psychology research literature, and has increasingly been applied to real settings and with authentic learning material.

What’s more, any such interventions - although they can help everybody - are likely to benefit to the lowest achievers most. This is simply because the less you have learned up to now, the greater the potential for improvement; the worse your study habits, the more you can improve them. In contrast, some other possible interventions tend to preferentially help higher achievers, for example more homework or smaller classes.

A major challenge, then, is to engage with the wealth of scientific research on memory that is out there, digest it, and communicate it in a way that teachers, learners and parents can actually use. There needs to be an increased psychological literacy when it comes to human memory - we need to understand how our own learning processes work, and how to use them better.

That is the aim of this blog.

The social brain hypothesis⤴

from @ Memory & Education Blog - Jonathan Firth

Did Lemurs' brains evolve to cope with their group size? Image by Erik Coolen.

Did Lemurs' brains evolve to cope with their group size? Image by Erik Coolen.

What caused human brains – and those of other apes – to grow so large? One theory is that it resulted from the complexity of our environment – the day to day problems that our ancestors would have encountered in foraging and survival: Where are the fruit trees? Which ones did I pick from yesterday?

Another idea – the social brain hypothesis – is that the complexity of our social groups require a big brain to keep track of, especially when the group is large. A bigger group means more relationships to remember.

Doing either of these things well could potentially lead to a survival advantage, but which actually triggered the evolution of our unique brain size? Dunbar (1992) put the two theories to the test by comparing both foraging area and group size with neocortex ratio – the proportion of brain neocortex to other brain areas (considered a better measure of overall ‘braininess’ than absolute brain size).

A clear correlation was found – a bigger group was associated with a larger neocortex ratio, supporting the social brain hypothesis. In contrast there was no clear relationship between brain size and environmental complexity. It would appear that primates with larger social groups need larger brains in order to keep track of relationships. That is not to say, as Dunbar comments, that those large brains couldn’t then be useful for dealing with environmental problems – but he does not feel it was the evolutionary driving force (Dunbar, 1998).

Human Groups

Since the early work with other primates, Dunbar began to question whether the same principle would apply to human social groups. To fit with the ratio that had been established, a group size of around 150 would be predicted (Dunbar, 1998). When we look at historical settlements, groups of around 120-150 members abound (Dunbar, 1993), and this is also the size of tribes in most hunter-gatherer tribes - the closest model we have of the lifestyle of our early ancestors.

In a neat application of the concept to the modern world, Hill and Dunbar (2003) looked at the size of networks to which people send Christmas cards. 153.5 was the mean total population of the households receiving cards from any individual - only a fraction over the predicted maximum number, and in practice, senders of cards would probably not know every member of a recipient household equally well.

More recently, other researchers have started to look at new technology and social media, to ask whether technological developments have expanded the size of our natural social network. It appears that they haven’t done so, at least not significantly – despite the large number of contacts people often establish on Twitter, the number they regularly communicate with remains under 200 (Gonçalves et al., 2011).


The key idea from the social brain hypothesis is that evolution has determined a cognitive limit on what we can do; just as we have other mental limits such as short-term memory capacity, the brain is simply not capable of maintaining a greater number of close social relationships.

What does this number mean in practice? An obvious question to ask is how close a relationship has to be to count within the number. Do colleagues and extended family count? Just how do we define who is in our 150 and who is not? According to Dunbar, a simple way to look at it is as “the number of people you would not feel embarrassed about joining uninvited for a drink if you happened to bump into them in a bar” (Bennett, 2013). If it truly is a biological limit, it could imply that we should avoid trying to continually extend our circle of friends/acquaintances, and instead foster stronger relationships with those that we are already close to.


Dunbar’s number does seem to be applicable to a large number of situations, from historic communities to hunter gatherer tribes, from the size of army units to Twitter engagement.

However not everyone is convinced. A correlation between brain size and social group size does not prove that there was an evolutionary cause-and-effect. And de Ruiter et al. (2011) have argued that although the neocortex plays an important role in social functioning, its size does not directly determine social skills.

It could also be argued that Dunbar has cherry-picked examples that fit the theory post-hoc, and that had the number from the correlation calculation been different (say 250), he would have been able to find examples of human communities to fit. Nevertheless, the idea that we do have a natural group size seems to fit the evidence of other species, and it makes a lot of sense to suggest that we can't push that limit beyond a certain point without impacting on the quality of the relationships.


Bennett, D. (2012). The Dunbar Number, From the Guru of Social Networks. Retrieved 20/11/2014 from: http://www.businessweek.com/articles/2013-01-10/the-dunbar-number-from-the-guru-of-social-networks

Dunbar, R.I.M. (1992). Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 22, 469-493.

Dunbar, R.I.M. (1993). Coevolution of neocortical size, group size and language in humans. Behavioural and Brain Sciences, 16, 681-735.

Dunbar, R.I.M. (1998). The social brain hypothesis. Brain, 9(10), 178-190.

Gonçalves, B., Perra, N. and Vespignani, A. (2011). Modeling Users’ Activity on Twitter Networks: Validation of Dunbar’s Number. PLoS ONE, 6(8): e22656. doi:10.1371/journal.pone.0022656

Hill, R.A. and Dunbar, R.I.M (2003). Social network size in humans. Human Nature, 14(1), 53-72.

de Ruiter, J., Weston, G. and Lyon, S.M. (2011). Dunbar’s Number: Group Size and Brain Physiology in Humans Reexamined. American Anthropologist, 113(4), 557–568.

#Flashbulb Memory by @TeacherToolkit⤴


How good is your memory? How much can you recall from your own schooling and can you think why this has stuck with you? Context: As I get to grips with writing my second book, I have been increasing the breadth and depth of my own research and re-thinking how memory can all be applied … Okumaya devam et

Jamie’s Flipped: (almost) a year with a flipped classroom⤴

from @ Pedagoo.org

There are lots of different ideas about Flipping your classroom, see this TED talk for more. But essentially you provide your learners with resources and videos to allow them to ‘learn’ the material as homework and then build on this with skills in your classroom. Starting in September 2013, and as part of my MSc research, I have […]