Letter to my Y13 Psychologists

Dear Y13 Psychologists,

This is a confusing and uncertain time for all of us, but especially so for people in your position. You have been working towards your A-Level exams for 13 years, since the first day you set foot in primary school. A-Levels give you the chance to demonstrate all that you have learned and the person that you have become in that period. It is therefore very, very sad that this chance has been taken away from you, and I am so sorry that this has happened. I’m also sorry that your time at school has been so cruelly cut short, taking away the chance to say a proper goodbye to a place that is of such importance and which you, in many cases, will have grown to be very fond of.

The first thing that needs to be said therefore is this. None of what you have done over the past two years is wasted effort. Even though it looks like you will never take an exam at the end of this, your learning will not have been pointless. The fact that you may not get to say it in an exam does not make anything that you have learned less valuable. Knowledge is always precious, and the more of it you have, the more doors that will be open to you in the future (and the more interesting you become as a person). You should treasure everything that you have learned over your time at school and be proud of it… and you certainly shouldn’t stop learning now just because your exams may not take place.

The best thing for you to do in the immediate future is to stay productive, active and positive as much as possible. You’ve studied the effects of isolation in the context of both prisons and attachment – so you don’t need me to tell you it can be a bad thing. Staying connected to others, and mentally challenged and switched on, is the best thing you can do for both your immediate self and your future self. It could, for example, be a great time to look at some university reading lists and select some of the most interesting looking books to order. But this could be a great time to also learn a new skill or to try a project that you’ve been putting off for a while. If you can’t already, learn to code a computer. Learn a musical instrument. See if you enjoy gardening. Go for a (socially distanced) jog in the park. Or just read all the books that A-Levels have made you too busy or tired to properly enjoy. Have a daily routine where you get up at the same time each day and make your bed. Sounds trivial but it means you’ve done two tasks already (and it makes you less likely to get back in!). Have a daily to-do list which you can tick off, and include even small social interactions (e.g. messaging a grandparent) on this list as well as your more academic jobs. Ideally do this in a small notebook so you can look back through and see how much you’ve accomplished with your time.

We don’t know what comes next in terms of grades, university applications and so on. It’s a complicated decision and to be honest I’m glad they’re not rushing it. It’s not a decision that we as individuals can have any control over, and so (although I know this is hard), you need to try put it out of your mind for the time being. Aim to control only the things that are in your control, and only worry about things that you yourself can directly affect. Anything else will just wear you down. It’s easy to catastrophize, but we have all been assured that you will get the qualifications in the end. The only questions that you need to worry about for the time being is this: whenever this is all over, will I look back and be proud of how I handled myself? Will I have used the time productively? Will I have helped myself and others?

Take care of yourselves, stay well, and good luck.

MHH

Letter to my Y13 Psychologists

Distance learning, habits, and revision. A letter to my Y12 Psychologists

Dear Y12 Psychologists,

These are strange times. You are about to become participants in the biggest experiment on distance learning that has ever been. Of course, as we can’t control the independent variable it’s technically a natural experiment, but you could have told me that!

In many ways I have more sympathy for your plight than for Y13 students. Their race is pretty much run, all that we need to do is work out what to do with the finishing line. For you, you’re only just getting started, and suddenly everything has changed. You’ve entered a marathon and it’s become a triathlon half way through… and we don’t know yet how long each section will be. That’s going to create enormous challenges for you, and for all other students in your position. It also creates opportunities. If you are able to adapt and remain productive, then there is no reason why this should negatively impact your learning. To prepare you for this, before we even think about how to cover the course content, I want you to know about when distance learning works (and when it doesn’t), and the skills that students require if they are to make it a success.

 

When distance learning works, and when it doesn’t

People have been offering distance learning courses for quite a while now, so we know a fair bit about when they work and when they don’t. Thousands and thousands of people sign up for online courses every day, for example. On average less than 13% actually complete them! So what is it that makes a successful distance learner? People have analysed the characteristics of successful learners (those who complete courses, compared to those who don’t – if you’re interested in this research you can read more here and here). Successful distance learners tend to:

  • Have time enough to complete the work
  • Have regular contact with the instructor
  • Be motivated
  • Have good working habits and routines

Time certainly shouldn’t be a problem for you guys! Contact with the instructor won’t be a problem either. I’ll still be setting work for you and am looking into online systems for providing feedback and sharing our progress as a group. Motivation is harder. Obviously it can be difficult to stay motivated in a distance learning environment, as you don’t have a teacher lurking over your shoulder asking you to do things (and giving you feedback when you do). Motivation can be especially difficult in times of uncertainty, although of course the end goal of what you are working towards (your A-Levels) hasn’t changed. Having said that, motivation becomes less important if you get the last of the things on the list right…

 

Habits and routines

I know that I bang on about habits and routines a lot, but if they were important before, then they are three times as important now. Schools, for all their faults and irritations to you as students, are brilliant at ensuring that your days are structured, varied and (mostly) productive. That is now down to you instead. You now have to be the person responsible for scaffolding your day in a way that makes the most of it. It’s a difficult task, one that many adults never properly manage if I’m totally honest, but it is possible, and the way to do it is by making your routine so familiar and standard that it just becomes what you do, without you even having to think about it. That is the amazing thing about habits, we do them automatically, without having to think or motivate ourselves to do them. They’re just what we do. If productive working becomes just what you do – just part of your everyday habits – then you don’t even really need to worry too much about motivation. These habits can be hard work to set up at first, but the rewards are huge. As we’ve seen above they are a crucial feature of high-performing and successful students.

Below is a graph of learning over time, after a switch to distance learning. The gaps between students with different habits get a lot wider. Working independently may actually not make much difference for students with the best routines. It will make a huge difference if you allow yourself to be a student without a routine. Don’t be that student.

distance learning

Creating the right working habits: making school at home

If you want to learn as well at home as you would at school, then it makes sense to adopt as many of the features of school as you can into your home environment. For example:

  1. Workspace. Do you have a clean, orderly space at which to work, like the desks at school? If not, then try to create one. Make sure your workspace resembles your school desk. You don’t have your phone out on your school desk, so don’t have it out at home. You don’t have loud music playing at school, so try not to have it playing at home (if you’re doing reading or writing, then music with lyrics is especially harmful – see here for a study on this if you’re interested). Although I know it might be hard if you have other siblings in the house, try as much as you can to minimise background noise and other distractions from people around you.
  2. Time management. In school your day is arranged into a timetable of hour long chunks… so why not do the same and create a home learning timetable that looks similar? It doesn’t have to follow your school timetable exactly, but as a rough guide at school you will spend on average about 1 hour each day doing each of your A-Level subjects. Aim for the same with your home timetable. Your teachers will be using this as a guide for the work we set you as well. You are, of course, free to work at the time of day that suits you best, but my personal recommendation would be to try to get three hours of work done in the morning. E.g. starting at 9am, and with a ten-minute break between each subject, you can have three hours’ work done by 12.20pm. Lunch, and one more hour’s work and you’ll be finished by 2pm!
  3. Chunk tasks, and set goals for each session. In a school lesson it’s rare that we work on a single task for the entire time. Usually it’s split (or ‘chunked’) into a series of smaller tasks, each of which has a clear aim and outcome. Try to do the same with your own home learning. Of course, this might be easy if the work you are sent already does this, but if it doesn’t then try to break the time into chunks, and give each chunk a clear aim. For example, instead of an hour of ‘revise Social Influence in Psychology’, you could instead have ’25 minutes – answer 20 quiz questions from the online textbook; 20 minutes – review answers and identify areas of weakness; 15 minutes – write flashcards on areas of weakness’.

 

Doing the right work. Revise and review

Another thing that is important over the next few months is the type of work that you do. Another common reason that people fail on distance learning course is because learning brand new material without a teacher is really hard. Being in charge of your own learning on a topic that you have no experience of is much harder than trying to improve on a topic that you already know something about. As a result, distance learning works best for revising what you’ve already covered, rather than learning lots of new material.

As it happens, we will need to cover some new material, as we still need to be progressing through the course, but we’ll do this very slowly. Much more important, as far as I am concerned, is that you take this opportunity to make everything that we have covered so far is completely secure. Whenever you return to school, it’s likely that we’ll have to cover quite a lot of new material. We will have absolutely no time to be re-teaching material that we have already done. In addition, whether you come back in the Summer, or September, or even later, you’ll be coming back to an assessment to help us finalise predicted grades. That will be based on work you’ve done so far, so you need to be ready for this. Your aim for the next few months should not be to practice until you can get the questions right, it should be to practice until you cannot get them wrong. I’ll be sending you more information on how I think you should do this in our first lessons next week.

 

You’re not alone

This will be a difficult time for all of us, with many distractions, worries and commitments that might draw us away from thinking about school work. I want to emphasise the importance of making time for your learning. Partly that’s because you’ll be examined on this stuff, but actually there’s a more important reason. Learning is a good thing in itself, and your education (although you may not always realise this now) is one of the most valuable things that you will ever be given, and something that you will treasure and be grateful for as long as you live. Value your learning, and the chances that you are given to learn, as highly as possible. I believe this very strongly, and that’s why I am absolutely determined to be with you every step of the way here. I’ll be in regular contact, and we’ll work out ways that groups of you can be encouraged to come together virtually as well. You are not alone.

So make a schedule, get a routine, and do some work. Not because you have to do exams, but simply because the more you know, the better and more interesting you will be as people, and the more you will be able to look back on this awful and difficult time and be proud of your reaction to it.

 

Take care of yourselves, stay well, and let’s get learning.

MHH

 

Distance learning, habits, and revision. A letter to my Y12 Psychologists

Attention in the classroom. My ‘best bets’ from the research

I’ve written before about why I think attention in classrooms is an area that both teachers and researchers should be more interested in. That blog is a few years old now, but I think is still a pretty accurate summary of what we know, given that it remains a fairly neglected research area (major influence on academic trends that I clearly have). I realised this week, however, that I haven’t ever written a slightly more optimistic counterpoint to that piece, detailing what I think teachers can infer from attention research, or at least where the jumping off points might be for teachers to begin exploring ideas in their own practice. Thanks goes to Mark Enser for providing the nudge needed to fill this gap. I’d love to hear other teachers’ strategies for maximising attention (I really recommend this blog from Ian Taylor, on a schoolwide system of ‘Track the Speaker’, for example).

 

Drawing tentative conclusions from patchy evidence

First, however, a quick note on the mindset I think is needed to interpret and start using some of this evidence. As I have said, evidence on the function of attention in classrooms, and how it might fluctuate, be controlled, or be improved, is very scarce. This is not like retrieval practice (with its hundreds of supporting studies across a range of learning environments). As ‘evidence-based’ practitioners, however, I don’t think that this should automatically mean that we don’t engage with areas where less research has been done. If we agree that no amount research evidence is a guarantee of success in a given classroom, and that evidence therefore represents the starting point in a developmental process rather than the end of the conversation, then we shouldn’t fear starting points that are a little further back. There are lots of reasons why research may not have been done which are nothing to do with the potential benefits it could have for some classrooms. With that in mind, therefore, here are the ‘starting points’ for teachers keen to consider attention more closely in their classrooms, based on my readings of the evidence available.

 

How distracted are students in the classroom?

Classroom distractions can come in a number of forms. In my PhD I took the not particularly inventive step of asking secondary school age students (Yrs 8-12) what sources had distracted them. Immediately after a regular classroom lesson they estimated the total duration of distraction they had experienced from different sources.

Screenshot 2019-03-01 at 10.41.45

Picture from (Hobbiss, 2019)

I think two main conclusions emerge from this graph. Students are distracted a lot of the time, by a wide variety of sources. This fits with older observational studies which found that elementary students spent between 25% and 50% of instructional time off-task (Karweit & Slavin, 1981). This clearly has implications for us as teachers trying to design and manage our classrooms. In my thesis we also found that performance on a laboratory task of attention control could predict these self-reports of lesson distraction (Hobbiss, 2019), so this does seem to be a feature that is related to the individual’s ability to control their attention, rather than simply reflect different lesson environments.

But what are the consequences of classroom distraction? And what should we as teachers do about it? Below are my ‘best bets’ for the classroom. Remember, this is only in terms of maximising attention control. You may use other techniques in order to achieve other goals. That’s entirely your prerogative as an informed teacher.

 

Background noise

Background classroom noise has been found to negatively impact reading comprehension and word learning in adolescents (Connolly et al., 2019) and may have some negative effects on creativity in children, depending on their initial attention control skills (Massonnié, Rogers, Mareschal, & Kirkham, 2019). It’s not clear whether noise needs to be above a certain level though (Connolly et al., 2019 found some suggestions of this), so it’s possible that relatively quiet background hubbub may not be too harmful, at least to some people. However, given how much we know that attention skills vary across the population (admittedly from numerous studies on adults but I see no reason why such variation would not also be present in childhood), it’s not clear at what level some noise may start to interfere for individuals with reduced attention control.

Best bet? If you have a task that will require any level of close concentration or careful thought, it is best to aim to have students do that in as quiet an environment as possible.

 

Displays

The function, and usefulness, of classroom displays is a source of perennial debate. High density of visual displays have been linked to increased time off task and reduced learning (Fisher, Godwin, & Seltman, 2014; Hanley et al., 2017; Rodrigues & Pandeirada, 2018), though these studies don’t always manage to accurately recreate classroom environments very satisfactorily. Also bear in mind that these studies don’t account for the probability that the distracting effect of displays over time will reduce as we become used to them (distractions in general are less potent the more predictable they are and the more habituated we are to them; Marsh, Röer, Bell, & Buchner, 2014), and as far as I know there is no research on displays that looks at their effect when they are regularly used as part of classroom routines, in which case they could easily become very useful. I would also note that in my thesis results (see graph above), displays were consistently the least reported source of distraction, so it may not be that they are actually the most pressing issue. Still, marginal gains are always worth looking for.

Best bet? I have removed all displays from the front half of my classroom (it was interesting to recently visit Heathfield CC in Sussex, where they have taken a similar approach). I would only make a display visible to the class if I knew that I would be referring to it regularly as part of a classroom routine.

 

Technology

The use of technology is an increasing feature of school classrooms, and already a ubiquitous one in higher education, where this has been more studied. Admittedly, we have to be careful in drawing links between studies done in university settings and schools (where the types of technology, programs available and functionality of the devices may be much more carefully regulated). However, there are still lessons to be drawn I think. Non-academic technology use (e.g. social networking, instant messaging, emailing or texting) has been consistently associated with poorer learning (e.g. Courage, Bakhtiar, Fitzpatrick, Kenny, & Brandeau, 2015; Flora Wei, Ken Wang, & Klausner, 2012; Kuznekoff & Titsworth, 2013; Risko, Buchanan, Medimorec, & Kingstone, 2013; Wood et al., 2012). Notably, the harmful effects of engaging in non-academic technology use during a learning session are not limited to the individual, but also negatively impact the learning of others for whom the screens are in their eyeline (Glass & Kang, 2018; Sana, Weston, & Cepeda, 2013). These negative effects are partially the result of distraction (e.g. by notifications, pop-ups etc) and partially through the illusion that we can multitask on a number of apps/tabs/functions at the same time (which many devices are designed to create). I’ve written before how the idea that any of us can efficiently multitask is an illusion, one that has increasing relevance and importance as technology steadily encroaches into ever younger classrooms.

Best bet? I’m not against tech in classrooms per se. Here’s an example I really like – the ‘Compare and Learn’ app. It can be an amazing tool. However, from an attention perspective there are clearly serious potential pitfalls. If I use tech in the classroom, I try to do so in an extremely tightly structured context, ideally using devices designed for educational purposes and so lacking many of the more diverting features often present on laptops, tablets and phones. I would certainly try to avoid very open-ended tasks such as simply ‘internet research’, as these are likely to open up far more opportunities for attention to be diverted. In general, even in my 6th form classes I also don’t allow note taking on laptops (tech distraction is associated with reduced note taking in general). If some students always have laptops or other technological learning aids and most of the class don’t then I try to seat them in a place where the screen will be least likely to distract others (e.g. on the back row)

 

Mindwandering

Tricky one this. Partly because we don’t even know it’s happening half the time, and partly because there doesn’t seem to be much that we can do about it even if we know it’s going on! There’s also some evidence that in environments where external distractions have been minimised (such as silent study rooms), distraction by mindwandering may increase (Robison & Unsworth, 2015), so simply eliminating distractions may not be a silver bullet for attention after all! It’s also amazing how prevalent mindwandering seems to be – nearly 10% of the time in my results from secondary classrooms (see above) and some studies have found it reported on up to 40% of the probes that they deliver! Some evidence does show a potential way forward, though perhaps not a clear one. For example, self-reported interest in the topic of study has frequently been found to be related to reduced mindwandering rates (Kane et al., 2017; Lindquist & McLean, 2011; Unsworth & McMillan, 2013). In my thesis I found that interest in the topic was significantly related to reductions in all distractions, but mindwandering most strongly. Theoretical models of mindwandering also predict that task engagement should be negatively associated with mindwandering (Smallwood & Andrews-Hanna, 2013; Smallwood & Schooler, 2015)

Best bet? Mindwandering can hopefully be reduced by increasing positive student engagement with the learning material or interest in the topic. Easy to say I know….!

 

Teacher talk

It is sometimes claimed that teachers should limit their amount of ‘teacher talk’ in lessons. One attention related justification for this is often that student attention spans are no longer than ten minutes, followed by a significant drop off in attention. The ten minute claim seems to stem from two studies from the 1970s. Johnstone and Percival (1976) conducted an observational study during undergraduate chemistry lectures in which observers made notes of physical signs of inattention such as diversions in gaze. They found that initial breaks in attention occurred after approximately 10-18 minutes. Even more commonly cited is a review by Hartley and Davies (1978), which is odd as this is actually a review of note taking in lectures. Even more oddly, the decline they noted was most common in the last ten minutes of a lecture rather than after the first. Meanwhile other evidence was finding contradictory results, for example Stuart and Rutherford (1978) actually found that medical student attention peaked around 10–15min into the lecture, although it but waned considerably thereafter. More recent research and reviews have consistently found that variations in attention do not follow the simple 10 minute rule. Within a general trend for decreased attention over time (usually over an hour’s lecture in a university setting), attention fluctuates considerably both within and between individuals, and dependent on other environmental variables such as the topic, student interest, instructional format and so on (see e.g. Bradbury, 2016; Bunce, Flens, & Neiles, 2010; Wilson & Korn, 2007). This more recent work has also demonstrated that individual differences in attention are far more important than any arbitrary ‘cut-off’ at which class attention might wane.

Best bet? If there’s something that you really need to explain clearly, and that explanation (or the story you want to tell) takes more that 10 minutes, then go for it (though attention is likely to wane after too long). It might be a good idea to at least try to break up your explanations though, partly if you suspect that individuals in your class may struggle with attention control, and also partly because…

 

Interpolated recall

In a recent article for the TES, Jenni Kemp and I outlined findings on an effect known as the ‘forward testing effect’. The forward testing effect involves the improved learning of new material after a test (i.e. material presented after the retrieval opportunity). In other words, providing recall opportunities seems to prime us to learn new information more successfully. There are a few possible reasons for this but the simplest may just be that the expectation of future testing makes learners concentrate a bit harder on new material. Experiments into this area often involve ‘interpolated testing’ designs, where small tests are interpolated throughout a learning session. Interpolating tests in this way seems to lead to improved learning of new material (Chan, Meissner, & Davis, 2018; Pastötter & Bäuml, 2014; Yang, Potts, & Shanks, 2018), but it has also been found that tested groups report improved attention (in the form of lower levels of mindwandering; Jing, Szpunar, & Schacter, 2016; Szpunar, Khan, & Schacter, 2013). Interestingly, in my own thesis, I managed to replicate a reduction in mindwandering after interpolated testing (in a university seminar), but the effect did not extend to external distractions (which weren’t significantly reduced by the testing; Hobbiss, 2019). This might be because of something as simple as the sample size or the range of distractions measured not being large enough, or it might be something more fundamental. We don’t know at present.

Best bet? Even if it only impacts on mindwandering, this would still seem a worthwhile aim (especially given how prevalent mindwandering tends to be in everyday life). I now think very carefully about whether any new information that I deliver to a class can be chunked into segments (a segment has in other educational literature been defined as “a block of time with a particular focus or intention”; Burns & Anderson, 1987, and I find that an helpful definition), and whether recall opportunities could be provided after each segment. The recall task does not necessarily need to be testing knowledge of the segment just completed (it could be for previous segments, or the lesson so far as a whole, or even other relevant synoptic material). I try not to stray too far from the main topic though, to avoid confusion.

 

Avoiding cognitive overload

Increased cognitive load makes people more susceptible to distraction (Carmel, Fairnie, & Lavie, 2012; Lavie, 2000, 2010; Linnell & Caparos, 2011), as a loaded working memory has more trouble maintaining goal focus and prioritising information. However, ‘measuring’ the load imposed by any situation is hard as it will vary for each individual, as will their ability to cope with it.

CAVEAT: I’m using ‘cognitive load’ in the sense it’s generally used in psychology and neuroscience literature, which doesn’t differentiate between ‘types’ of cognitive load as in Sweller’s Cognitive Load Theory in education. I know that there are lots of enthusiastic debates about the validity and value of CLT. I’m not worried about those here. My concern is the implications of cognitive load (in general) for attention.

Best bet? I now aim to break my instructions down into chunks of one or two steps at a time. Dual-coding instructions or information can also help reduce cognitive load. I am also a big fan of graphic organisers, which allow schemas to be laid out visually, and let me as a teacher pre-structure aspects of a student’s thought process. All these should prevent cognitive overload, and hopefully positively impact attention.

 

Any potent sources of distraction that I’ve missed? Please do get in touch.

 

References:

Bradbury, N. A. (2016). Attention span during lectures: 8 seconds, 10 minutes, or more? Advances in Physiology Education, 40(4), 509–513. https://doi.org/10.1152/advan.00109.2016

Bunce, D. M., Flens, E. A., & Neiles, K. Y. (2010). How long can students pay attention in class? A study of student attention decline using clickers. Journal of Chemical Education, 87(12), 1438–1443. https://doi.org/10.1021/ed100409p

Burns, R. B., & Anderson, L. W. (1987). The Activity Structure of Lesson Segments. Curriculum Inquiry, 17(1), 31–53. https://doi.org/10.1080/03626784.1987.11075276

Carmel, D., Fairnie, J., & Lavie, N. (2012). Weight and see: loading working memory improves incidental identification of irrelevant faces. Frontiers in Psychology, 3, 286. https://doi.org/10.3389/fpsyg.2012.00286

Chan, J. C. K., Meissner, C. A., & Davis, S. D. (2018). Retrieval Potentiates New Learning : A Theoretical and Meta-Analytic Review. Psychological Bulletin, 144(11), 1111–1146.

Connolly, D., Dockrell, J., Shield, B., Conetta, R., Mydlarz, C., & Cox, T. (2019). The effects of classroom noise on the reading comprehension of adolescents. The Journal of the Acoustical Society of America, 145(1), 372–381. https://doi.org/10.1121/1.5087126

Courage, M. L., Bakhtiar, A., Fitzpatrick, C., Kenny, S., & Brandeau, K. (2015). Growing up multitasking: The costs and benefits for cognitive development. Developmental Review, 35, 5–41. https://doi.org/10.1016/j.dr.2014.12.002

Fisher, A. V., Godwin, K. E., & Seltman, H. (2014). Visual Environment, Attention Allocation, and Learning in Young Children: When Too Much of a Good Thing May Be Bad. Psychological Science, 25(7), 1362–1370. https://doi.org/10.1177/0956797614533801

Flora Wei, F. Y., Ken Wang, Y., & Klausner, M. (2012). Rethinking College Students’ Self-Regulation and Sustained Attention:Does Text Messaging During Class Influence Cognitive Learning? Communication Education, 61(3), 185–204. https://doi.org/10.1080/03634523.2012.672755

Glass, A. L., & Kang, M. (2018). Dividing attention in the classroom reduces exam performance. Educational Psychology, 0(0), 14. https://doi.org/10.1080/01443410.2018.1489046

Hanley, M., Khairat, M., Taylor, K., Wilson, R., Cole-fletcher, R., & Riby, D. (2017). Classroom displays- attraction or distraction? Evidence of impact on attention and learning from children with and without autism. Developmental Psychology, May 4.

Hartley, J., & Davies, I. K. (1978). Note‐taking: A critical review. Innovations in Education & Training International, 15(3), 207–224. https://doi.org/10.1080/0033039780150305

Hobbiss, M. H. (2019). Attention, Mindwandering and Mood: relating personal experiences in daily life and in the classroom to laboratory measures. UCL, UK.

Jing, H. G., Szpunar, K. K., & Schacter, D. L. (2016). Interpolated testing influences focused attention and improves integration of information during a video-recorded lecture. Journal of Experimental Psychology: Applied, 22(3), 305–318. https://doi.org/10.1037/xap0000087

Johnstone, A., & Percival, F. (1976). Attention Breaks in Lectures. Education in Chemistry. Retrieved from https://eric.ed.gov/?id=EJ136799&gt

Kane, M. J., Smeekens, B. A., von Bastian, C. C., Lurquin, J. H., Carruth, N. P., & Miyake, A. (2017). A Combined Experimental and Individual-Differences Investigation Into Mind Wandering During a Video Lecture. Journal of Experimental Psychology-General, 146(11), 1649–1674. https://doi.org/10.1037/xge0000362

Kuznekoff, J. H., & Titsworth, S. (2013). The Impact of Mobile Phone Usage on Student Learning. Communication Education, 62(3), 233–252. https://doi.org/10.1080/03634523.2013.767917

Lavie, N. (2000). Selective attention and cognitive control: Dissociating attentional functions through different types of load. In S. Monsell & J. Driver (Eds.), Control of cognitive processes : Attention and Performance XVIII (p. 779). MIT Press. Retrieved from https://books.google.co.uk/books?hl=en&lr=&id=kO_baYlSVbwC&oi=fnd&pg=PA175&dq=Selective+attention+and+cognitive+control:+Dissociating+attentional+functions+through+different+types+of+load.+In+Attention+and+performance+&ots=ps5GMKknT3&sig=4FcFWfVmkZCtHgQCf

Lavie, N. (2010). Attention, Distraction, and Cognitive Control Under Load. Current Directions in Psychological Science, 19(3), 143–148. https://doi.org/10.1177/0963721410370295

Lindquist, S. I., & McLean, J. P. (2011). Daydreaming and its correlates in an educational environment. Learning and Individual Differences, 21(2), 158–167. https://doi.org/10.1016/j.lindif.2010.12.006

Linnell, K. J., & Caparos, S. (2011). Perceptual and cognitive load interact to control the spatial focus of attention. Journal of Experimental Psychology: Human Perception and Performance, 37(5), 1643–1648. https://doi.org/10.1037/a0024669

Marsh, J. E., Röer, J. P., Bell, R., & Buchner, A. (2014). Predictability and distraction: Does the neural model represent postcategorical features? PsyCh Journal, 3(1), 58–71. https://doi.org/10.1002/pchj.50

Massonnié, J., Rogers, C. J., Mareschal, D., & Kirkham, N. Z. (2019). Is Classroom Noise Always Bad for Children? The Contribution of Age and Selective Attention to Creative Performance in Noise. Frontiers in Psychology, 10(February), 1–12. https://doi.org/10.3389/fpsyg.2019.00381

Pastötter, B., & Bäuml, K. H. T. (2014). Retrieval practice enhances new learning: The forward effect of testing. Frontiers in Psychology, 5(APR), 1–5. https://doi.org/10.3389/fpsyg.2014.00286

Risko, E. F., Buchanan, D., Medimorec, S., & Kingstone, A. (2013). Everyday attention: Mind wandering and computer use during lectures. Computers & Education, 68, 275–283. https://doi.org/10.1016/j.compedu.2013.05.001

Robison, M. K., & Unsworth, N. (2015). Working Memory Capacity Offers Resistance to Mind-Wandering and External Distraction in a Context-Specific Manner. Applied Cognitive Psychology, 690(July), 680–690.

Rodrigues, P. F. S., & Pandeirada, J. N. S. (2018). When visual stimulation of the surrounding environment affects children’s cognitive performance. Journal of Experimental Child Psychology, 176, 140–149. https://doi.org/10.1016/j.jecp.2018.07.014

Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education, 62, 24–31. https://doi.org/10.1016/j.compedu.2012.10.003

Smallwood, J., & Andrews-Hanna, J. R. (2013). Not all minds that wander are lost: the importance of a balanced perspective on the mind-wandering state. Frontiers in Psychology, 4, Article 441. https://doi.org/10.3389/fpsyg.2013.00441

Smallwood, J., & Schooler, J. W. (2015). The Science of Mind Wandering: Empirically Navigating the Stream of Consciousness. Annual Review of Psychology, 66(1), 487–518. https://doi.org/10.1146/annurev-psych-010814-015331

Szpunar, K. K., Khan, N. Y., & Schacter, D. L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures. Proceedings of the National Academy of Sciences, 110(16), 6313–6317. https://doi.org/10.1073/pnas.1221764110

Unsworth, N., & McMillan, B. D. (2013). Mind wandering and reading comprehension: Examining the roles of working memory capacity, interest, motivation, and topic experience. Journal of Experimental Psychology: Learning Memory and Cognition, 39(3), 832–842. https://doi.org/10.1037/a0029669

Wilson, K., & Korn, J. H. (2007). Attention During Lectures: Beyond Ten Minutes. Teaching of Psychology, 34(2), 85–89. https://doi.org/10.1080/00986280701291291

Wood, E., Zivcakova, L., Gentile, P., Archer, K., De Pasquale, D., & Nosko, A. (2012). Examining the impact of off-task multi-tasking with technology on real-time classroom learning. Computers and Education, 58(1), 365–374. https://doi.org/10.1016/j.compedu.2011.08.029

Yang, C., Potts, R., & Shanks, D. R. (2018). Enhancing learning and retrieval of new information: a review of the forward testing effect. Npj Science of Learning, 3(8), 1–9. https://doi.org/10.1038/s41539-018-0024-y

Attention in the classroom. My ‘best bets’ from the research

How do we know when other people need to know what we know? On scientific purity, useful fictions and evidence in the classroom

In a great series of recent threads (started here, and subsequent discussions here, here and here, amongst others), Matt Slocombe, from Birkbeck University has been arguing against the ‘politicisation’ of cognitive science evidence in recent education reforms, and looking to build a consensus of researchers who might seek to influence the direction of future decision-making. Specifically, Matt objects to the central importance given to Cognitive Load Theory (CLT), and the consequent absence of evidence from other sources within cognitive or developmental psychology, in new teaching frameworks, such as the initial teacher training and early career frameworks (you can read more from Matt and colleagues on this here).

I know Matt a bit and am always impressed by his passion, drive and breadth of knowledge. Also, in the way that you can only have really interesting discussions with people with whom you generally concur, I agree with a number of his criticisms. I do, however, have some reservations regarding some of the implications of this push to influence policy.

 

Scientific criticisms of a model are not de facto criticisms of its applied value

In his tweets, Matt lays out some of the major criticisms against CLT as a model of cognition. Others have also been a consistent voice pointing out weaknesses with some of the underlying theoretical assumptions (and research methodology) of CLT, such as Christian Bokhove. I’ve also pointed some of these out in the past, for example being quoted with my PhD supervisor in this TES article that was generally critical of CLT (though I should say that I didn’t agree with the conspiratorial tone that the author eventually took or his interpretation of some of our comments). I’m certainly not arguing, therefore that the CLT model is entirely accurate, or even that it isn’t severely deficient in some respects. The question is, how much does this matter?

Given that no-one involved in this debate would presumably expect teachers to be as informed as researchers in this area, we’d all then accept that teachers’ understanding of cognition will always be based on models – imperfect approximations of the truth. The question, then, is how harmful is it to have a model that is slightly too ‘rough’, (or conversely, how much does it really benefit teacher to have a model that is slightly more accurate)? It is likely that diminishing returns will be at play here – ever increasing scientific knowledge will not lead to ever increasing skill at implementation. Indeed, having just finished a four year PhD and now preparing to go back into the classroom in January, I can attest that there can be a certain level of ‘evidence paralysis’ that can set into planning when you are too aware of all of the drawbacks of every theory going! So where is the line, which will improve outcomes for students in the classroom, without burdening the teacher with too much in the way of niche scientific debate? We don’t know. We don’t have studies on the effects of a widescale adoption of practices informed by a slightly simplistic model of CLT in classrooms. We might in ten years, given the new ITE frameworks, but at present we’re pretty much clueless about the ideal level of sophistication for teachers’ understanding of the science of learning.

As a result of this, while I am perfectly happy for people to criticise aspects of the underlying theory of CLT, and to argue for a slightly more nuanced or broader evidence base to be covered in initial teacher training, I think it is less easy to state with any certainty that the current model of CLT is likely to be harmful for teachers or students, and that it therefore should be changed. We simply don’t know this. It’s also not clear how closely the scientific criticisms affect many of the parts of the theory that teachers actually use. For example Damian Benny, in a reply to Matt here, acknowledges some of the criticisms of the theory, but argues that the valuable applications to the classroom are not really affected by them. Others have also commented that, even if a ‘strong’ reading of the CLT model might be interpreted as suggesting that content knowledge is prioritised entirely above any other skills such as creativity or problem solving (an interpretation that I don’t fully buy into), this isn’t how the theory is being used in classrooms anyway.

CLT, as with all models, is a ‘useful fiction’. How useful, and how fictional, remain to be seen. I can’t therefore accept that it can be dismissed with any certainty.

 

Developmental research is not de facto relevant to education

A related second point concerns the idea that current frameworks are insufficient, because they are limited in the evidence that they cover. In Matt’s original thread he refers to “a rich body of relevant cognitive and developmental evidence being ignored”. Of course, developmental psychology is historic and rich subject, which has revealed many fascinating aspects of human development. I would contend, however, that there is no automatic reason to suppose that developmental findings will be relevant to educational practice, and in fact there is very little evidence which we can currently state with certainty is something that ‘teachers need to know’. Remember here that the debate is not about what we would ideally like the most enthusiastic, informed teacher to know, but rather what it should be necessary for teachers to know, as mandated by training frameworks and government policy. In order to qualify for that high bar (especially given the limited bandwidth available for this in amongst all the other things trainee teachers need to learn), research needs to do two things:

  • Tell teachers something that they are not already aware of from other sources.
  • Provide teachers with clear guidelines for how their practice might be adapted

If these criteria are met, then learning in more detail about the underlying mechanisms and developmental processes is justified. For perfectly good reasons, however, very few (in fact I’d say almost no) developmental studies reach this bar. That’s simply not what the scientific studies are designed to do.

Let’s take an example, based on my own PhD research looking at distraction in adolescents in the classroom. Three years ago I blogged about what we know about attention during adolescence, pulling out two key messages, that adolescent attention is inconsistent, and that it is disproportionately biased during these ages towards interference from motivational or emotional stimuli, and by things such as their peers. There is a lot of ingenious and hugely impressive work by researchers that has explained many of the neuroscientific processes behind these conclusions… but what does this mean for teachers? Do teachers not already know that teenagers are inconsistent, easily distracted (especially by their peers) and emotionally volatile? Hardly. Do teachers need telling that reducing distractions in classrooms is probably a good idea? Hardly. I’d therefore argue that developmental work on adolescent attention fails both of the criteria above. In another nice example of this recently, Nick Rose examined attachment theory – a psychological theory examining relationships between children and their parents or caregivers – and its relationship to teaching practice. He concluded that the main implications of attachment theory for teachers – that they should aim for good relationships with students and that they should pass on safeguarding concerns to people trained to deal with them – is exactly what teachers already do. As a result, the theory is of limited use in terms of its applications for teachers.

Matt has put together a site of cognitive and developmental science research which he thinks might to inform educators and education policy. I think that this is a fabulous idea and have suggested some contributions, but the papers included did rather reinforce my view that there is very little research around there at the moment with direct, clear classroom applications which do not simply confirm what teachers already do. To my mind, this is less to do with politics, and simply a reflection of the chronic lack of translation studies, which take cognitive findings and examine how they can best be applied in real classrooms. In the absence of such findings, we have no way of knowing which research teachers need to know, and which they don’t. If we aren’t happy with the use of CLT in policy, then it’s unfortunately incumbent on the researchers to demonstrate that other ideas are as valuable, if not better. We can’t do this at present.

At the heart of this is a philosophical debate about how ‘good’ evidence has to be for scientists to be happy to put it forward to influence policy and practice. Clearly no piece of evidence is ever perfect, nor any theory beyond reproach, so if we prevaricate for too long searching for absolute certainty then we’ll never influence anything. My personal feeling, however, is that if we as researchers are to start applying our knowledge across disciplines, such as into education, then we need to be pretty damn sure that our suggestions actually work in that new environment, and that they can be easily and successfully implemented into classrooms. I just don’t think we’re there yet.

Which is probably why I’ll never end up influencing anything.

How do we know when other people need to know what we know? On scientific purity, useful fictions and evidence in the classroom

Constructivism is a theory of learning, not a theory of pedagogy. Neuroscience explains why this is important

Unsurprisingly, teachers are very interested in the brain, and excited about the potential for psychology and neuroscience evidence to be used in improving what they do (see for example the responses to this survey). It’s a shame, then, that so little time in many teacher training routes has traditionally been given over to psychology and the science of learning. Especially if you trained five or more years ago (as I did), it seems to have been very rare to have received more than a cursory introduction to the subject… apart from one notable exception. However little psychology gets covered otherwise, one mandatory inclusion on many teacher training courses is constructivism — the idea that every individual constructs their own understanding and knowledge of the world, based on their own unique experiences. As a result, constructivist ideas are undoubtedly the most widely held ‘folk-psychological’ belief about learning amongst current teachers (See Torff, 1999, and Partick & Pintrich, 2001 for more on the content of teacher training and changes in trainee teachers’ beliefs about learning).

In this post I am going to argue that this state of affairs is dangerous. Importantly, though, the problem is not that constructivism is wrong. Constructivism works well as a theory of learning. The problem comes, however, when it is assumed that the theory of learning implies a particular pedagogical approach (‘educational constructivism’, or sometimes the closely related approach of ‘constructionism‘). Using evidence from neuroscience, I will try to show that there is a great deal of support for constructivism the learning theory, and a good deal less for constructivism the pedagogical approach.

Some of the misapplications of constructivism to pedagogy have been well documented before. Phillips (1995) described ‘The good, the bad, and the ugly‘ of constructivist pedagogy, and Hyslop-Margison & Strobel (2007) put a slightly more nuanced slant on the same topic. Much of their focus is on the potential for more radical constructivist views to lead to a relativistic approach to knowledge in which, because knowledge is individually constructed, there is ‘your knowledge’ and ‘my knowledge’ and little scope for any external validation.

My focus here, however, is on the extent to which the operations of the brain, especially during development, can help us to see why constructivism the learning theory does not entail the pedagogy. I’ll use the evidence underpinning the theory of ‘Neuroconstructivism’ (Mareschal et al., 2007), one of the most popular theories of developmental cognitive neuroscience, to help me with this.

Partial representations, and context-specificity

A central feature of neuroconstructivism is that the development of our brains and the storage of information in them is hugely context-dependent. At any one moment, activity in the brain is a reflection of the context that the organism finds itself in. Mareschal et al., provide four different levels where the activity of the brain is constrained by the context in which it occurs: neural, network, bodily and social. We’ll look at examples of context-specificity for each of these in turn in a minute. The important point, though, is that brain activity reflects the precise state of the organism at the time of the event, so any new piece of ‘learning’ will be encoded completely within the context of the learning experience, rather than reflecting any general underlying feature of it. In the terminology of the theory, we are only ever able to create ‘partial representations’; representations of the world which capture some, but not all of it. Partial representations are, by their very nature, completely context-dependent; that is, they reflect the features of the world (and of the brain) which were the case when the information was originally stored. Let’s then look at the four levels which can lead to the creation of such ‘partial’ representations. This section is heavily paraphrased from a previous description of the theory, but I reproduce it here for clarity.

  1. Neural context – ‘encellment

The cellular neighbours of a neuron exert a large influence over its eventual function as a processor of information. The characteristics of its response and the way in which it connects and influences other neurons is in turn dependent on the type and amount of activity that the neuron itself receives. One classic example is that “cells that wire together fire together” — the more that cells communicate with each other, the more that their connections are strengthened, and the greater influence that a preceding cell exerts over the activity of subsequent cell.

However, the context-dependence of neural activity is not limited to the simple co-operative strengthening of connections. They can also compete. Hubel and Wiesel’s Nobel Prize-winning work on vision in cats involved looking at what happened if a part of the brain called the visual cortex was understimulated (because they had covered up the eye which sent information to it). They found that after 2-3 months, the nerve cells in the understimulated area began to switch functions and process information from the uncovered eye instead.

So what?

The activity of any one neuron is context-specific. This context is constantly changing due to a number of different factors: the ever-changing strengths of connections to potentially thousands of other inputs, competition (or co-operation) between neighbouring cells, or a progressive specialisation of the cell’s function. Therefore a signal from a neuron can only be interpreted as representing that cell’s response to a particular set of circumstances at that specific time; the neural context.

Another consequence of the reliance of each neuron’s activity on so many of its neighbours is that this means that any information that is encoded by the neuron is likely to be done so in a distributed fashion, across large groups of neurons. Such ‘distributed representations’, whilst more robust on the face of damage and brain changes, are also far more likely to be ‘partial representations’, relying as they do on numerous small contributions from different neural sources. They will never capture a concept or an idea in its entirety. Instead, they record a blurred snapshot of some of the key details approximating the concept, a partial representation.

 

2. Network context – ‘embrainment’

Just as individual neurons can be affected by the context in which they find themselves, so entire brain areas can co-operate, compete and change function as a result of their context within the brain as a whole. On a larger scale than that noticed by Hubel and Wiesel, Cohen et al (1997) found that in people who have been blind from an early age, ‘visual’ cortex begins to take on other functions entirely, such as touch when reading braille. Similarly, if you re-route visual information into a ferret auditory cortex (an area that would normally deal with processing sounds), the area will begin to respond to visual patterns instead (Sur and Leamey, 2001)! In less drastic fashion, maturation in the brain involves the progressive specialisation of many different brain areas, which gradually take over sole control of functions that previously relied on wider networks. Again this process can be categorised by competition, with one area gradually coming to exert a dominant influence over a particular kind of processing. Good examples of these sorts of processes have been found in the pre-frontal cortex (PFC) during adolescence, with different sections of that brain area becoming ‘responsible’ for particular functions.  (see Dumontheil, 2016 for some examples).

So what?

Most formal education is taking place during periods of rapid brain development and maturation. Brain areas are progressively specialising and refining their functions, dependent on their relationship to other brain areas and input from the outside world. In this context, the distributed and partial representations that we build of the world are likely to be highly context-dependent, not only on the particular pattern of inputs, but also on the time and stage of development in which the information was learned.

 

3. Bodily context – ‘embodiment

The brain does not sit in glorious isolation from the rest of the body. Some hard-wired nervous behaviours, such as reflexes, can in fact form the basis for the beginnings of brain development. Infants make spontaneous reaching movements from an early age and even new-born infants will move their limbs to block a light beam (Van der Meer et al, 1995). These kinds of behaviour initiate the beginnings of feedback mechanisms between the visual and motor areas of the brain and eventually allow for the development of complex visually-guided behaviour. Of equal importance, the design of some parts of the body can constrain brain development by ensuring that it does not need to develop certain skills; cricket ears are designed to respond preferentially to male phonotaxis (a sound made by rubbing one wing against the other). The cricket brain has no such specialisation for making this distinction, because the job has already been done (Thelen et al., 1996). In human cognition, examples of ‘embodiment’ might include state-dependent memory; the finding that we recall information more successfully in a similar ‘state’ to when we learned it, for example after exercise (Miles and Hardman, 1984) or even when drunk (Goodwin et al., 1969).

So what?

The development of our brains is constrained and uniquely differentiated by our nervous systems and by the body in which we find ourselves. Again, this is not just the case between individuals but also within individuals as they develop over time, and as they pass through the myriad different internal states which characterise our existence. The representations that we have of the world will reflect these changing embodiments, and will be ‘partial representations’ in that they are formed, and linked to, this embodied context. This therefore provides further scope for learning to be constrained by the situation (in the widest possible sense) in which the information was initially encountered. The Goodwin et al. paper is particularly relevant here, as it tested two outcomes; recognition and transfer. They found that, whilst recognition memory was not significantly affected by the a change in states between learning and recall, the ability to transfer the information was. Transfer, as a more complicated cognitive procedure than simple recall, is as a result even more susceptible to being restricted by the context in which it occurs.

 

4. Social context – ‘ensocialment

The concept of ensocialment, the idea that the social context for any act of learning is crucial to shaping the learning that takes place, will be the most familiar of these four levels of analysis to educators. Vygotsky’s social constructivist theories are probably the most famous educational application of this sort of idea. People learn from others with more skills than them; with the more knowledgeable mentors using language and guidance to ‘scaffold’ the learner’s interactions with the world in the most productive manner. The concept of scaffolding; a supportive structure which is gradually removed as the learner gains in ability, is used to one degree or another by almost every major educational approach.

So what?

The type of scaffolding that is used may become inextricably linked to the solution that is produced, to the point where the ‘partial representation’ that we have of the solution is not accessed when the problem is framed differently. In one famous example, children working in Brazilian markets were able to demonstrate mathematical strategies on their stalls that they could not do in the classroom. Knowing how to do something in one context is no guarantee of being able to demonstrate the same skill in another.

 

Neuroconstructivism and constructivist learning

This brief survey has aimed to show how our experiences in the world can only ever lead to context-specific, partial representations of these events in our brains. It should hopefully be immediately clear that this evidence fits very well with many of the main ideas of constructivism as a theory of learning. The constructivist idea that meaning and knowledge are created by the individual in response to their specific experiences and ideas clearly fits very comfortably with the notion of partial representations. Given that each individual will have their own unique neural, network, bodily and social context at any one moment, even the same environmental stimulus is likely to lead to different partial representations of that stimulus in different people.

The neuroscientific evidence also complements the ‘constructive’ aspect of learning very nicely: the building up of ever more complex schemas through the gradual formation of multiple, overlapping partial representations of the world. It also appears to explain the focus of at least some constructivist theories (e.g. Piaget and Dewey) on the individual, highlighting the unique individual context in which any act of learning takes place. Indeed, the individual context is so important that, as we have seen, learning will often not transfer to contexts (even seemingly very similar tasks and environments) which do not share enough of the original features.

 

Neuroconstructivism and constructivist pedagogy

So far so good. Unfortunately, it has been common practice in education to go a step further, and to assume that the theory of learning implies/favours a particular pedagogical approach. Because constructivism emphasises the unique individual context in which learning takes place (and the individual’s role in the construction of that knowledge), so constructivist pedagogy places the onus on the individual student to construct their own understanding of the world. Teachers are therefore encouraged to design learning environments through which students are able to learn for themselves, sometimes facilitating the learning, but generally providing limited explicit guidance. Because constructivism emphasises the ‘active construction’ of knowledge, so constructivist pedagogy often places increased value on hands-on, ‘active’ or experiential learning (such as by experiment, project or solving real-world problems). This will, naturally, be entirely familiar to any teachers reading this post. If your teacher training was anything like mine, it will have been exactly how you were taught to teach.

Unfortunately, the leap from learning theory to pedagogy is not justified. Constructivism, as conceived purely as a theory of learning by Piaget, was not designed to be associated with any specific pedagogical approach. More importantly, the raft of neuroscientific evidence supporting the theory of ‘neuroconstructivism’ actually, in my view, provides strong evidence to suggest the opposite, that constructivist pedagogies are unlikely to be the most effective approaches to learning, at least until schemas are well developed.

 

Partial representations, and constructivist pedagogy 

Let us return to ‘partial representations’, those context-dependent neural traces which constitute how the brain changes in response to experience. As we have seen, these traces are:

  • partial – in that they reflect not the underlying structure of the knowledge but the whole neural, network, bodily and social context in which the knowledge was formed.
  • distributed – in that they are made up of numerous small contributions from neurons distributed across brain areas. No one piece of information therefore resides in any one place, and any reactivation of that knowledge will be an approximate reconstruction, rather than a video-tape playback.
  • context-dependent – as the knowledge contained in our partial representations often does not transfer to situations.

What relevance does this have for pedagogy? Well, let us take a constructivist-inspired pedagogical approach, which involves minimal explicit guidance being given to a student. Imagine a child over the course of a lesson discovering – through some trial and error and some careful teacher-facilitation in a thoughtfully structured learning environment – the formula for Pythagoras’ theorem. It sounds like a lovely educational experience for both student and teacher. Unfortunately, at the end of this process we have (time-consumingly) produced but a single partial representation, which is likely to be highly susceptible to context-dependency.

What the neuroscience of learning tells us is that in order to increase the likelihood of them being more easily accessed subsequently, students require multiple, overlapping partial representations, which are strengthened through repeated access. In his book ‘The Hidden Lives of Learners‘, Graham Nuthall wrote that students need to encounter information three or four times to learn it, and with the idea of multiple, overlapping partial representations we can see why such repeated exposure to information is so important. From this perspective, it is not the discovery of the strategy which is important for subsequent success, but the repeated exposure to it, and practice at accessing it, multiple times and in multiple different ways. There is therefore nothing wrong with the student learning about Pythagoras in the way described above, provided that they are subsequently afforded repeated opportunities to revisit and practise their new knowledge in different contexts. The problem is that, all too often, demonstration of a skill in the learned context is taken as indicating mastery of the skill in general, so lessons move on after a limited number of demonstrations of any new idea. Neuroconstructivism clearly shows that under such circumstances, we are unlikely to form enough overlapping partial distributions to be able to transfer our knowledge to a new context.

 

‘Neuroconstructivist pedagogy’: Multiple, overlapping, partial representations

What I have tried to show above is that our representations of the world, by their very nature, are only ever ‘partial’ representations. Given that, it makes sense for educators to work to create as many of them, and to strengthen them, wherever possible. So is there a particular pedagogical approach that is specifically favoured by the neuroscientific evidence? No. I should be clear I do not think that neuroscience findings can ever be used to directly conclude that any one pedagogical method is better than others. I do, however, think that the evidence underpinning neuroconstructivism provides some important considerations which different pedagogical approaches can all benefit from taking into account. These considerations are encapsulated in the statement:

Students require multiple, overlapping, partial representations of knowledge in order to transfer it to new contexts.

Given that having knowledge that we are able to transfer to a new context is pretty much the point of education itself, I think this is an important message. Again, however, I am not arguing here in favour any one pedagogical approach. I have my personal preferences, but I want to keep this separate from what I think the neuroscience evidence objectively tells us. The creation of multiple, overlapping, partial representations could conceivably be achieved through numerous pedagogical approaches, as long as students have the opportunity for repeated exposure to information and multiple chances to apply new knowledge to different contexts. It could be achieved through more explicit or direct instruction methods, through dialogic approaches, through well-structured co-operative or group strategies, even (if you have enough time spare in your curriculum) through repeated overlapping inquiry-style investigations such as the one described earlier. What teachers need to consider is, in their own context, which (combination of) teaching methods is most likely to produce repeated exposure to knowledge, and practice at applying it to different contexts. What this looks like in each classroom is a decision for each individual teacher.

So there we go. Some people are sceptical that neuroscience has anything to offer education. I agree that the neuroscientific evidence doesn’t provide support for any one concrete strategy of instruction (indeed, I don’t think it ever could). I think it does, however, create a simple and powerful question that I continue to ask myself as I evaluate how I teach. It is also a question that I wish I had been asked right at the start of my teaching career. So… how are you going to ensure that you form multiple, overlapping, partial representations?

 

 

Constructivism is a theory of learning, not a theory of pedagogy. Neuroscience explains why this is important

Bridge of Sighs. My thoughts on reading yet another paper on the relationship of neuroscience and education

When John Bruer wrote his seminal 1997 paper ‘Education and the brain: A bridge too far’, arguing that the potential of neuroscience to directly influence education was limited, I imagine that he would not have anticipated two aspects of the subsequent debate over 20 years later. The first surprise would be that the substantive points of the debate have hardly moved on at all over that time. A great deal of ink has been spilled by those who agree with Bruer’s scepticism (e.g. here, here, here, here and here) and those who are more optimistic (here, here, here, here, here, here and here), but for the most part they have tended to talk past one another, relying on different characterisations of what a ‘neuroscientific application to education’ actually entails (prime example of this to come). The second surprising consequence of Bruer’s article has been to spawn a whole academic sub-genre of papers about education and neuroscience with ‘bridge’ related titles. We’ve had calls to ‘build bridges’ (e.g. here and here), ‘envisioned bridges’, ‘boundaries as bridges’ and (most enjoyably), ‘bridges over troubled waters’.

https---upload.wikimedia.org-wikipedia-commons-thumb-b-b2-Bridge_Astore.jpg-1024px-Bridge_Astore

A paper just published in Current Directions in Psychological Science is the latest addition to both exhibits. In ‘Neuroscience and Education: A Bridge Astray’, Michael Dougherty and Alison Robey argue that,

Although we acknowledge the value of neuroscience for understanding brain mechanisms, we argue that it is largely unnecessary for the development of effective learning interventions. We demonstrate how neuroscience findings have failed to generalize to classroom contexts by highlighting the recent popularity and failed results from brain-training research

As this summary suggests, the paper contrasts brain training, an apparent example of an ineffective educational intervention from neuroscience, with more effective educational interventions from cognitive science, for example memory strategies such as spaced retrieval. Unfortunately, this comparison does not stand up to a great deal of deeper scrutiny. I’ll address first my specific concerns with the paper, before trying to show how I found many of the points in the paper symptomatic of my frustrations with much of the previous literature, on both sides of the argument.

 

Building bridges, or building silos?

One of the key assumptions of arguments on the sceptical end of the educational neuroscience debate is that it is possible to very clearly demarcate between research disciplines, e.g. that there is a clear boundary between neuroscience and cognitive psychology. This is obviously essential if you are planning to claim that neuroscience cannot influence education, but psychology can. The problem is that this demarcation is increasingly difficult to perform. The ever-expanding field of cognitive neuroscience explicitly blurs the boundaries between the cognitive and the neural, with each (in theory) reciprocally informing the other. Dougherty and Robey are therefore left with a bit of a dilemma in terms of how to separate ‘neuroscientific’ interventions, from ‘cognitive’ interventions. Their answer is to latch onto some foundational neuroscientific ideas (brain plasticity and synaptogenesis), and to argue that these concepts have not been translated into any useful educational interventions. This is already somewhat shaky ground as pretty much every brain process relies on brain plasticity, including of course the memory changes caused by the interventions based on cognitive theory which they are using as a contrast. However Dougherty and Robey seem want to differentiate interventions which have been initially inspired by neuroscience evidence, as opposed to those initially inspired by cognitive/behavioural evidence. It’s still a difficult and slightly artificial balancing act, but we will accept it for the time being.

 

Their demonstration of an intervention ‘inspired’ by neuroscientific evidence (and also, therefore, their example of the failure of neuroscience to be able to influence education) is the case of ‘brain training’. Brain training interventions (i.e. training on one or more cognitive tasks with the aim that this generalises, or “transfers,” to improved performance on other cognitive tasks and to daily life) has generally been found to be ineffective (see e.g. here, here, here, here and here). With this I am in absolute agreement with the authors. They then write, however:

Brain training is emblematic of the gulf between basic neuroscience and education, wherein seemingly groundbreaking neuroscience findings (e.g., brain plasticity, synaptogenesis, pruning) simply do not scale up to practical education interventions

Is this casual alignment of ‘brain training’ and neuroscience merited? For starters, as the authors themselves point out in the article, ‘brain training’ interventions are just as often called ‘cognitive training’ or ‘working memory training’! This seems somewhat odd if the origin of such training programs can (as the authors seem to claim) be so clearly linked back to purely neuroscientific findings, rather than cognitive psychology, or (whisper it quietly), a mixture of the two. It’s an example of the need for some opponents of educational neuroscience to silo off research disciplines into mutually exclusive territories in order to contrast them; a view which is becoming increasingly difficult to sustain in the face of interdisciplinary research fields such as developmental cognitive neuroscience. Their claim also, however, relies on two key assumptions, which merit dealing with in some more detail.

 

  1. Is ‘brain training’ “emblematic” of educational neuroscience?

The answer to this is a very clear no. There is a huge range of work being done at the moment under the broad banner of ‘neuroscience and education’, and brain training is, frankly, but a tiny fraction of this work. Some of these projects I am very excited about, others cause me concern. For example, I think that far too many ‘educational neuroscience’ projects are designed with little understanding (or interest) in the realities of everyday educational environments. I have taken issue with the unwarranted application of neuroscience into areas of education where it has no business before (e.g. here), and argued that the immediate role of neuroscience in education is not to create brand new, flashy pedagogies or tools, but to help us understand and critique the ideas that are already in use in the classroom (e.g. here and here). In summary I am no evangelist for the idea that ‘educational neuroscience’ research will always produce educational benefit, but I can recognize a misrepresentation of a broad research area when I see one. Treating brain training as “emblematic” of attempts to use neuroscience to improve education is exactly that.

 

  1. Is ‘brain training’ really a neuroscientific idea?

A central part of the argument of Dougherty and Robey is that the interest in ‘brain training’ can be traced directly from basic neuroscientific research findings. I question this assumption. As we have seen already, the fact that brain training is also just as often called cognitive training or working memory training, already raises some doubts as to how purely ‘neuroscientific’ this idea is. Beyond this, however, I would argue that the hypotheses behind brain training are not actually supported by basic neuroscience research and theory, and therefore that the claim that it is a ‘direct neuroscientific intervention to education’ is false. At best, perhaps, it is a ‘direct intervention to education based on a misrepresentation of neuroscience evidence’, but that is rather less catchy. In actual fact, the idea that brain training would be an effective intervention is incompatible with a good deal of what we know about how the brain operates.

Brain training programs rely on the idea of ‘cognitive transfer’, the idea that knowledge or skills learned in one context can be applied to another context (for example, that someone who has improved their ability to do working memory tasks will, as a result, also be better able to do mental arithmetic). Unfortunately, a very large amount of evidence attests to the fact this this is not, in fact, how the brain works, and that brain activity is often stubbornly, frustratingly, context specific. In the influential developmental theory of ‘neuroconstructivism’, for example, context specificity is taken as a central feature of how the brain operates (I have described neuroconstructivism in more detail previously). This means that at all levels, from the neural to the environmental, the activity of the brain is dependent on the context that it finds itself in. Individual neurons compete and constrain one another’s activity. Brain networks do the same, The state of our bodies and the environmental context at the time all also determine the activity of our brain in response to any specific event. In such a system, any neural trace is merely a ‘partial representation’, a representation of the world which captures some, but not all of it. Partial representations are by definition hugely context specific, they record the precise state of the organism at the time of the event, rather than any general underlying feature of it. This means that they don’t generalise very well to other contexts. In one great example (from Karni et al., 1995: note, well before the existence of any ‘brain training’ programs), learning a sequence of movements in one order was found not to transfer to improved learning of a sequence of the same movements in a different order. Given results like this, we should hardly be surprised when brain training programs fail to show transfer to much more distant cognitive abilities.

Dougherty and Robey seem to suggest that brain training programs are a logical extension of neuroscientific findings. I would argue that, in actual fact, a raft of neuroscientific evidence supports the opposite conclusion, that changes in the brain are often context-dependent, and as a result form only partial representations of the world which do not effectively transfer to new contexts.

 

The journal’s gain is teaching’s loss

A lot of water has flowed under the bridge since Bruer first erected it, but I feel that Dougherty and Robey’s article illustrates many of the wider reasons why little progress has been made. A straw man of a ‘neuroscience intervention’, unnatural and forced demarcations between subject areas, strange definitions of what the ‘success’ of a neuroscience intervention would look like (here, successful cognitive transfer, in other cases ‘brand new pedagogical ideas’). Both sides are responsible for these, for example I have been critical (as indeed are the authors of the article), of attempts to co-opt findings which were clearly initially the result of cognitive or educational psychology as ‘educational neuroscience’, based on the fact that we have subsequently done a few brain scans which back up the original findings1. Perhaps the name ‘educational neuroscience’ itself is inadvertently creating some of this tension, suggesting a primacy of neuroscience over psychology. In truth this is not the view of anyone working in the field that I am aware of, but the perception may remain. It is partly for this reason that American researchers have tended to use the more accurate (though less pithy) title ‘Mind, Brain and Education Science’ when referring to the same field.

The sadness in this logical and semantic squabbling is that is has real world consequences. Teachers are genuinely interested in, and keen to learn about, findings from neuroscience and psychology which may be relevant to their practice (Simmonds, 2014). In the absence of any coherent messages from academia (and whilst journals happily lap up publication fees for articles from either side) other voices slide into the void offering ‘brain-based’ solutions to teachers which may be at best ineffective, and at worst downright harmful.

http---www.chinatoday.com-entertain-china.funny.pictures-funny_picture_2012_13-943-broken_bridge
The bridge which REALLY needs attention is the one to education

The real priority: the collapsed bridge to education

In truth I don’t think it actually matters at all which academic silo/s your data was created in. The debates above are spending time arguing about the order of the traffic, without noticing that the only bridge that is genuinely important here, the one between academia and education, is in a terrible state of repair. The pressing issue, for all parties, is that we still have no coherent framework for translating research findings into educational applications, and hence no clear system for actually finding out which research actually isbeneficial to education, and which is not. Translating research to the classroom is a challenging and complex task, and just as neuroscience findings shouldn’t be applied direct to classrooms, neither should cognitive psychology ones. Amongst other things, any promising research result will need to be adapted, ideally in collaboration with teachers, to create an intervention which is practical (for use in different classrooms and by different teachers), beneficial (i.e. producing outcomes that are of direct relevance and interest to a teacher) and valid (retaining scientific rigour and the ability to be evaluated for effectiveness).  At present, however, there exists almost no formal guidance or research on how this process can best be achieved to the mutual benefit of all parties. This is, for me, a far more important issue than to debate the philosophical implications of bridges between different subject areas.

Only with a proper framework for translating research into practice will we be truly able to see which neuroscientific or psychological findings will translate into valuable educational interventions and which will not. Results will be inconsistent; such is the nature of trying to apply research to the messy real world. I’d love to see it happen, though I wouldn’t like to predict which ideas will prove the most impactful. We’ll just have to cross that bridge when we come to it.

 

Footnote:

1A prime example might be the spacing effect in memory (the idea that information is more effectively learned in a number of spaced sessions than in one go, first reported by Herman Ebbinghaus in 1885), whichis currently under investigation in schools as a project funded by an ‘Education and Neuroscience’ research grant, despite the findings almost pre-dating psychology, let alone neuroscience.

Bridge of Sighs. My thoughts on reading yet another paper on the relationship of neuroscience and education