Tag Archives: research

Five lessons I’ve learned about genetics

I admit that I began reading to find evidence that supported my view. I was sure science would back me up. And then I, complete with a list of Harvard-format references, would win the next debate. The problem was that science didn’t agree with me. I could find pockets of supporting evidence, but the overwhelming consensus was that I was wrong. It made me phenomenally uncomfortable to see a consensus emerging that directly contradicted my beliefs about how the world should be. But ultimately, science is not about how the world should be. Science is about how the world is. And if I want to make it different, I need an accurate picture of how it is now.

This is a blog on reading about genetics – what I’ve learned, and what I want to do about it. The lessons are the things that struck me as a teacher most, and are largely based on reading about intelligence or other cognitive characteristics. I want to note up front that I am not an expert, and that writing this is part of my attempt to learn more. If and when I’ve made a mistake please let me know and I will rectify it as quickly as possible.

Lesson #1: Genetics explains much more of the variation between people than I was willing to accept
The most influential type of study for this blog is the twin study, which looks to explain the variation between people and attribute it to one of three categories of cause: the shared environment (factors that would be common to a pair of twins living in the same household and attending the same school); the non-shared environment (all other environmental factors); and genetics. Studies of cognitive ability tend to find that variation is 10-20% shared environment, 30-40% non-shared environment, and 50-60% genetics.

This was hard for me to accept. I wanted to believe that most variation is caused by things within our control. Instead the shared environment, of which school is only one part, explains under a fifth of the variation between people.

Before moving on to Lesson #2 it is important to stress that we are talking about variation here – not absolute levels. We can say that 50% of variation in intelligence is genetic in origin, we can say nothing about how much of your intelligence is caused by your genes.

Lesson #2: Environments change how genes are expressed
Your genetic code is fixed, but what you do with it isn’t. Geneticist Nessa Carey likens your genetic code to the script of a play, which is then interpreted extensively by the actors and director before becoming the performance that eventually appears on stage. Epigenetics is the study of these interpretations, which are as crucial to our biological functioning as the genetic code itself.

One thing we learn from epigenetics is that our environment shapes how we interpret our genetic code, and that these interpretations stick. Once we have scrawled annotations over our genetic script they will stay unless we actively rub them out – and when our children inherit our scripts they will find many of our annotations still in place.

Extreme or consistent environmental stimuli can create epigenetic modifications that change how your genes are expressed. For example, a stressful environment can lead to genes that control the production of cortisol (a stress hormone) becoming over-expressed, meaning that you become much more easily stressed in the future. Such a change will then persist, shutting off chunks of working memory and reducing executive function in years to come.

As many epigenetic modifications are heritable it is difficult for twin studies to separate their effect from the effect of genes themselves, and so it is possible that some of the causal impact of genetics is actually environmental in origin. As our ability to do more complex analysis with the genome itself increases we will no doubt find out whether this possibility means anything in practice.

Lesson #3: Environments correlate with genes
A tall child is more likely than a short child to be asked to try out for the basketball team. Where we may have a genetic propensity towards a certain area we tend to seek out (or be pushed towards) an environment that increases that propensity. This means that a small effect that begins life as just an inkling of interest or talent can easily grow into a specialised environment that exaggerates initially small effects. It is possible that correlations like this are responsible for a significant proportion of our genes’ impact. If we adapt environments, whether consciously or not, we will be magnifying genetic differences.

Lesson #4: Genetics does not determine outcomes
Twin studies observe the differences we see today and explain their origins. They do not have any say in how big these differences are or will be in the future. So the fact that 50% of variation in a characteristic is due to genetic causes today does not mean that it must be tomorrow. Nor does it mean that we must accept present levels of difference as necessary. The numbers we find in these studies are not natural constants.

Behavioural geneticist Robert Plomin says that studies tell you what is, not what could be. He likens our genetic understanding of intelligence to our understanding of weight. Whilst it is obviously the case that people can be genetically predisposed to put on more or less weight than each other, it is also true that with the right interventions almost anybody can achieve a healthy weight. The same is true for intelligence. There may be genetic predispositions, but we can make sure that everybody achieves an acceptable level by providing the right environment.

Lesson #5: Genetics assumes determinism
If a study assumes that all difference is caused by either genetics, the shared environment or the non-shared environment, then it is also making one other underlying assumption: that everything about a person has an external cause. It assumes that your intelligence or success is a function solely of your genes and your environment. But what if everything about us is not 100% deterministic?

I was hesitant to write this lesson down, for fear of seeming to criticise the entire body of work genetics has given us. Science has to operate by studying the relationship between cause and effect. I cannot challenge it for failing to account for independent free will. But I am nonetheless uncomfortable not accounting for it. I do not know nearly enough in this area to do anything more than speculate. But I do wonder whether the large influence of the non-shared environment, that bucket for everything we can’t put our finger on, may be substantially down to things like attitude and motivation that may not be fully caused by an external mechanism.

So what do I take from all this?
Firstly, that genetics plays an unquestionably big role in explaining who we are, and how our brains work. Even if some of the effect attributed to genes is in fact environmental in origin (due to epigenetics or gene-environment correlations) there is no doubt that genes have a huge influence.

But secondly, even though genes make us all different, they don’t determine our cognitive future. Long-term memory still has unlimited capacity; brain plasticity is still immense; and good teaching can still take advantage of this. Genes determine difference, but they’re no excuse for educational inequality.

Why homework is bad for you

Laura McInerny’s third touchpaper problem is:

“If you want a student to remember 20 chunks of knowledge from one lesson to the next, what is the most effective homework to set?”

After a day of research at the problem-solving party, I came to this worrying conclusion:

Setting homework to remember knowledge from one lesson to the next could actually be bad for their memory.

So stop setting homework on what you did in that lesson – at least until you’ve read this post.

Components of Memory

Bjork says that memories have two characteristics – their storage strength and their retrieval strength. Storage strength describes how well embedded a piece of information is in the long-term memory, while retrieval strength describes how easily it can be accessed and brought into the working memory. The most remarkable implication of Bjork’s research surrounds how storage strength is built.

Storage and Retrieval strength – courtesy of Kris Boulton

Retrieval as a ‘memory modifier’

Good teaching of a piece of information can get it into the top left hand quadrant, where retrieval strength is high but storage strength is low. Once a chunk of knowledge is known (in the high retrieval sense of knowing), its storage strength is not developed by thinking on it further. Rather storage strength is enhanced by the act of retrieving that chunk from the long-term memory. This is really important. Extra studying doesn’t improve retention. Memory is improved by the act of retrieval.

The ‘Spacing Effect’

Recalling a chunk of knowledge from the long-term memory strengthens its storage strength. However for this to be effective, the chunk’s retrieval strength must have diminished. ‘Recalling’ a chunk ten minutes after you’ve studied isn’t going to be very effective, as your brain doesn’t have to search around for such a recent memory. Only when a memory’s retrieval strength is low will the act of recall increase storage strength. This gives rise to the spacing effect – the well-established phenomenon that distributing practice across time builds stronger memories than massing practice together. 

Rohrer & Taylor (2006) go a step further and compare overlearning (additional practice at the time of first learning) with distributed practice. They find no effect of over learning, and ‘extremely large’ effects of distributed practice on future retention.

Optimal intervals

There is an optimal point for recalling a memory, in order to maximise its storage strength. At this point, the memory’s retrieval strength has dropped enough for the act of retrieval to significantly increase storage strength, but not so much to prevent it from being accurately recalled. Choosing the correct point can improve future recall by up to 150% (Cepeda, et al., 2009).

There has been a common design of most studies into optimal spacing. Subjects learn a set of information at a first study session. There is then a gap before a second study session where they retrieve learned information. Before a final test there is a retrieval interval (RI) of a fixed time period. Studies such as Cepeda, et al (2008) show that the optimal gap is a function of the length of the RI, and that longer RIs demand longer gaps between study periods. However this function is not a linear one – shorter RIs have optimal gaps of 20-40%, whereas longer RIs have optimal gaps of 5-10%.

Better too long than not long enough

Cepeda et al’s 2008 study looks at four RIs: 7, 35, 70, and 350 days. The optimal gaps for maximising future recall were 1, 11, 21 and 21 days respectively, and these gaps improved recall by 10%, 59%, 111% and 77%.

Perhaps their most important finding is the shape of the curves relating the gap to the future retention. For all RIs these curves begin climbing steeply, reach a maximum, and then decline very slowly or plateau. The implication is that when setting a gap between study periods it is better to err on the side of making it too long than risk making it too short. Too long an interval will have only small negative effects. Too short an interval is catastrophic for storage strength.

Why homework could be bad

Homework is usually set as a continuation of classwork, where students complete exercises that evening on what they learned in school that day. This constitutes a short gap between study sessions of less than a day. We know that where information is to be retained for a week, the optimal gap is a day, and that where this is not possible it is better to leave a longer gap than a shorter one. For longer RIs, the sort of periods we want students to remember knowledge for, the optimal gap can be longer than a week.

Therefore, if you want students to remember information twenty chunks of knowledge for longer than just one lesson to the next, the best homework to set is no homework!

Setting homework prematurely actually harms the storage strength of the information learned that day by stopping students reaching the optimal retrieval interval. In this case, students who don’t do their homework are better off than ones who do!

Why I might be wrong, and what we need to do next

There is not enough good evidence of how to stagger multiple study sessions with multiple gaps. For example, we do not know where it would be best to place a third study session, only a second. However we do know that retrieval is a memory modifier, and so additional retrieval should strengthen memories as long as the gap is sufficiently large for retrieval strength to have diminished. Given we know that retrieving newly learned information after a gap of one day is good for storage strength, it may be that studying with gaps of say 1, 3, 10 and 21 days are better for storage strength than a solitary study session after 21 days, where the RI is long (350 days or greater). In this case for teachers who only have one or two lessons a week, homework could help them make up the optimal gaps by providing for study sessions between lessons.

The optimal arrangement of multiple gaps is a priority for research. We need to better understand how these should be staged, so that we can begin to set homework schedules that support memory rather than undermine it. Until then, only set homework on previously learned knowledge, and better to err on the side of longer delays. My students will be getting homework on old topics only from now on.


Joe Kirby on memory this weekend
EEF Neuroscience Literature Review
Dunlosky, et al., 2013. Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology
Rohrer & Taylor, 2006. The Effects of Overlearning and Distributed Practise on the Retention of Mathematics Knowledge
Cepeda, et al., 2009. Optimizing Distributed Practice
Cepeda, et al., 2008. Spacing Effects in Learning: A Temporal Ridgeline of Optimal Retention
Everything Kris Boulton writes