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This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
SCIENCE, PSEUDOSCIENCE AND EXERCISE NEUROSCIENCE: UNTANGLING
THE GOOD, THE BAD, AND THE UGLY
Richard Bailey, ICSSPE, Berlin
Introduction
The chapters in this book have sought to review current state and status of exercise neuroscience,
and particularly to examine how this rapidly developing field might inform decisions about
educational practice. Some chapters are technical, and report on the results of scientific
experimentation, whilst others are more applied. However, the contributions have been informed
by a recognition of the need to move research beyond the ivory tower into real-life settings,
addressing key questions about the ways in which the emerging knowledge of the brain can help
teachers and other educational practitioners. This is likely to be an on-going task, facilitated by a
reciprocal interaction between scientific research and practical knowledge.
Recent years have seen new research methods that have led to remarkable progress in the
understanding of the neurological basis of human cognition and learning. For example, in 2011,
fewer than 750 published scientific articles used findings from functional magnetic resonance
imaging (fMRI) on the human brain. By the beginning of 2017, there were 32,500 fMRI studies
reported in the PubMed database. fMRI and other imaging techniques have allowed researchers
to look inside the living brain, creating images that locate regions of activity associated with
specific cognitive tasks, as well as revealing structural differences among individual brains
(Passingham, & Rowe, 2015). Detailed understanding of the biochemistry of brain, intra-cellular
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
recording, pharmacological interventions and other technologies have also developed at an
accelerated pace (Pokorski, 2015). Combined with psychological research, these studies have
greatly improved the understanding of the basic processes that underlie capabilities such as
numeracy, literacy, attention, memory, and social interaction (Immordino-Yang, 2016;
Mareschal, Butterworth, & Tolmie, 2014). Understandably, these advances have sparked a great
deal of interest in the possibility to improve learning and education using brain research,
especially among teachers (Pickering & Howard Jones, 2007; Serpati, & Loughan, 2012). In an
era of evidence-based practices, the new educational neuroscience seems an enthralling prospect.
The authors of a highly influential report from the Organization for Economic Co-operation and
Development (OECD) interpreted the scientific basis as the neural base, and asked whether “it is
acceptable, in any reflection about education, not to take into consideration what is known about
the learning brain” (OECD, 2007, p. 28). Scientists tend to be rather more cautious of making
bold claims preferring to wait for more and better evidence (e.g., Della Sala, 2009; Goswami,
2014). However, the excitement surrounding this area of research is palpable.
It may well be the case that the relationship between physical activity and educational
performance is one area of research capable of generating genuine insights for practice (Bailey,
2016). This has been hinted at by authors from the broad field of educational neuroscience,
within which exercise neuroscience could be partly located (e.g., Dekker, Lee, Howard-Jones, et
al, 2012). But here, as in other areas of applied neuroscience, there exists a perennial risk of the
intrusion of dubious claims and practices. This chapter discusses the danger the phenomenon of
pseudoscience, which is ideas or practices that seek to resemble real science but which fails to
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
follow its guiding principles. Specifically, this chapter focuses on the intrusion of pseudoscience
into educationally orientated activities, including physical activity and movement. Pseudoscience
shadows real science as bird excrement sticks to statues, and it is argued that it presents serious
difficulties for those seeking to move towards evidence-based practice in schools.
One way of thinking about this situation is in terms of ‘the good’, the bad’, and ‘the ugly’. Good
research follows the procedures of the scientific method, with its established methods, analyses,
checks and balances. Bad research fails to follows the protocols of the scientific method in some
significant ways. Ugly research is bad, but adds an important additional element: it harms the
people to whom it is exposed. The risk of ugly science in the context of health is obvious,
leaving patients worse off or even dead as result of ‘quack’ treatments (Singh & Ernst, 2008), but
there are serious risks in education, too. The presence of bad and ugly neuroscience in the
classroom is problematic because it wastes money, time, and effort, which might be better spent
on the development of evidence-based practices.
What is the appeal of so-called ‘brain-based’ claims for schools? Has the growth of brain-based
theories and practices outside of mainstream academic science been a useful development, a
harmless distraction, or positively risky for children’s education and well-being? In seeking out
answers to these questions, this chapter examines some of the most popular brain-based ideas
and products that are currently being used in schools around the world, focusing on those that
include aspects of physical activity and movement. It asks whether there is sufficient quality
evidence to justify their place, which requires some discussion about the nature of evidence,
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
science, and its unreliable alter-ego, pseudoscience. The rise and spread of pseudoscience, it is
argued, threatens the integrity and development of education, and is a genuine cause for concern
that requires addressing by teachers, scientists, and policy makers. The chapter concludes by
suggesting some strategies for addressing this problem, and to ensure that students in schools are
exposed to ideas and practices based on science, not nonsense.
The Appeal and Danger of Brain-based Approaches in Education
Historically, the relationship between educational practice and empirical science has been an
uncomfortable one. Difficulties in making meaningful connections between practice and
evidence are not restricted to education, of course, and numerous fields, from sports coaching to
medicine are struggling with similar concerns (see, for example, Fulford, 2008). This is not to
suggest that there is not a broad consensus that these areas should be informed by evidence, but
there appears to be much less agreement about what this means in practice. For example, there is
widespread interest among teachers, parents and policy makers in the application of
neuroscientific research findings in educational practice. One study found that almost 90% of
teachers in the UK considered knowledge of the brain functioning to be relevant for their work
(Pickering & Howard Jones, 2007). In some circles, interest has morphed into a ‘neuromania’
(Legrenzi, & Umilta, 2011), or a general sense of optimism that understanding the brain will help
solve many previously intractable educational and social problems. It seems, though, that a
general receptiveness to the idea of neuroscience has not yet translated into changes to practice
in classrooms. More accurately, the combination of interest in all things ‘neuro’, and the
persistent difficulty of finding meaningful connections between scientists and practitioners has
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
created a fertile space in which a plethora of so-called ‘brain-based’ products, of highly variable
scientific quality, have flooded into schools (Coch & Ansari. 2012). Many teachers who have
been exposed to such materials assume a direct link between their often-ambitious claims and
genuine science (Goshwani, 2014). However, unlike real science, pseudoscience typically offers
simple solutions to problems that routinely challenge teachers in classrooms.
It is important to stress that these concerns are not merely academic. To claim that a theory or
practice is scientific is to present them as possessing a degree of value and credibility. In
practice, it means that there is an implication that those ideas have been rigorously debated,
refined, and tested, and that they have survived that process. The science writer, Carl Sagan
(2011), captures the spirit of science when he wrote: “At the heart of science is an essential
balance between two seemingly contradictory attitudes--an openness to new ideas, no matter
how bizarre or counterintuitive they may be, and the most ruthless sceptical scrutiny of all ideas,
old and new. This is how deep truths are winnowed from deep nonsense” (p. 304). The label of
science does not indicate certainty or proof, but it does point to a provisional survival of a
process of repeated, critical discussions, and ruthless experimentation. Untested ideas that use
the language and imagery of science seek to leech of the credibility of science.
The translation of scientific research into practice is always going to be a challenge. Science is
not simplistically prescriptive; it is primarily descriptive. In order words, science seeks to learn
the truth about the world as it exists independent of human observation (Psillos, 1999); it is not
particularly qualified, not typically willing to, advice about the practical or moral implications of
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
its findings. So, even the most valid and reliable research findings cannot be applied into the
schools without serious consideration of the multiple factors that influence student learning and
the inherent social complexity of schooling (Bailey, 2015). A difficulty that is specific to the
neurosciences is that adding even meaningless references to the brain makes claims more
persuasive (Weinberg, Kell, Goldstein, et al, 2008). The field of neuroscience is complex and the
accurate transfer of research findings to the classroom is often difficult (Devonshire and
Dommett, 2010). This gap between neuroscience and education has enabled many
misconceptions about scientific findings to occur (Goswami, 2006). In 2002, the OECD drew
international attention to this phenomenon. The organization raised concerns with regards to the
rapid proliferation of so-called “neuromyths”. These were defined as “a misconception generated
by a misunderstanding, a misreading, or a misquoting of facts scientifically established (by brain
research) to make a case for use of brain research in education and other contexts”. There is little
doubt that neuromyths abound in education, and their popularity has proved a major obstacle for
disseminating genuine neuroscience (Fischer, 2009).
Many neuromyths are patently absurd, such as the suggestion that people generally use only 10%
of their brain’s capacity (cf. Geake, 2008). Presumably, part of the appeal of such beliefs lie in
their promise of extraordinary potential change. Indeed, numerous films have been premised on
precisely this beguiling thought: if a way to use more of the brain could be discovered, lives
would be transformed. That many people seem to believe such ideas says a great deal about the
power of appealing ideas to trump awkward scientific details (people using 10% of their brains
would be registered brain-dead). Indeed, an early study examining neuroscientific knowledge in
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
the general population of Brazil reported that the 10% neuromyth was the most prevalent
misconception among the public (Herculano-Houzel, 2002). Likewise, the misinterpretation of
laterality studies to produce so-called ‘left- and right-brained thinking’ appears to rely for its
appeal of the potential benefits that would follow its realisation. There are countless products
currently being sold to schools and parents that that promise to facilitate some sort of integration
of the left and right hemispheres of the brain, and many of these involve movement-based
practices (such as ‘Brain Gym’, which will be discussed later). However, these products are
based on a serious misunderstanding. The original laterality studies were of patients who had the
major communication tract between the two brain hemispheres, the corpus callosum, surgically
severed to reduce life-threatening epilepsy. Over time, the predicament of these poor people has
somehow become generalised to the claim that almost everyone’s head contains two relatively
independently operating brains, and suffers from a communication breakdown between these two
hemispheres. Moreover, it is usually claimed, only some special technique can get the two brains
talking to each other again. Scientific understanding of the brain continues to grow, but the brain
does not consist of two hemispheres operating in isolation (Eagleman, 2015). In fact, the
different specialties of the left and right hemisphere are so well-integrated that processing
problems almost never occur. Creative thinking, the most common context for discussions of
left- and right-brained thinking, is particularly dependent on interaction of both sides, as neither
one can operate in isolation from the other. In fact, connectivity, not isolation, best-characterises
the operation of the normal human brain (Mayringer, & Wimmer, 2002).
Another popular product is Neuro-linguistic Programming (NLP; Bandler, & Grinder, 1979). As
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
the name suggest, NLP clearly aspires to align itself to the neurosciences, despite the problematic
detail that it was developed before the current understanding of the brain took shape, and has
retained much of its original content. Bandler and Grinder were mathematics student and
linguistics lecturer respectively, and their lack of background in any discipline connected to the
scientific study of the brain is a further concern. Nonetheless, NLP is hugely popular, and its
claims that eye movements give insight into thought processes, that certain language patterns can
subliminally influence others’ behaviour, and that the skills of experts can be learned with
relative ease by identifying and coding their unconscious thought processes, have bled into sport
psychology, teacher education, professional development, talent identification, and other areas
(Lazarus, & Cohen, 2009; Carey, Churches, Hutchinson, et al, 2010; Hippolyte, & Théraulaz,
unknown1). A survey of British National Governing Bodies for sport found that NLP content
1 The last reference - from a soccer magazine - is one of the very few published sources on ‘The
Action Type Approach’, a collection of supposedly brain-based practices, including the Myers-
Briggs Type Indicator (MBTI), learning styles, and movements reminiscent of ‘educational
kinesiology’. This model seeks to provide insight into the training of athletes “to take it to the
next level”, by integrating on “natural movement” (Action Types, 2013). As is common with
such brain-based products, the claims made on behalf of the Action Type Approach are
impressive, which might explain why it has been adopted by numerous elite sports groups,
including the England Cricket team and a number in international football clubs (Action Types,
2013). Unfortunately, not a single research article could be found on this method, and direct
requests to the creators and leading advocates resulted in no other sources of research evidence.
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
could be found on most coach education programmes (Bailey, 2013).
The scientific status of NLP is controversial, and this is largely due to a disjunction between the
often extremely ambitious claims made on its behalf by advocates and the relative lack of serious
research in support of those claims. The academic response to NLP has generally either been to
either dismiss or ignore it (Witkowski, 2010). Beyerstein (1990) wrote that "though it claims
neuroscience in its pedigree, NLP's outmoded view of the relationship between cognitive style
and brain function ultimately boils down to crude analogies" (p. 27). A Delphi study (a survey of
experts’ opinions) listed NLP among “discredited psychological treatments” (Norcross, Koocher,
& Garofalo, 2006), and NLP is frequently included in lists of questionable or pseudoscientific
methods (e.g., Tardif, Doudin, & Meylan, 2015).
Some supporters have responded by claiming that the evidence base for NLP is much stronger
than critics present. Perhaps the most noteworthy of these responses is the ‘research paper’ by
Carey, Churches, Hutchinson, et al (2010). Part of the interest in this document is that it was
published by CfBT Education Trust, and organisation that has been closely involved with the
delivery of aspects of UK Government educational policy. The report begins with what is
erroneously called a systematic review of the literature (erroneous, because none of the standard
protocols for this specific type of review are followed, including explicit inclusion/exclusion
criteria and search strings, the use of multiple databases, and independent validation)2.
2 The EPPI Centre at UCL Institute of Education, London lists the key features of a systematic
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
After dismissing the relevance of “occasional critical academic commentaries”, the authors
summarise their sources:
• Journal articles (including articles that were not peer-reviewed);
• Conference papers;
• “Articles which had some form of university affiliation and articles whose writers had
some form of university affiliation or track record in research”;
• Papers connected to government programmes and which presented evaluation data;
• Postgraduate level research findings (both at Masters and Doctoral level);
• Practitioner findings published in journal articles and papers with some element of
university or recognised research organisation affiliation.
The result of this search strategy is a collection of findings, the great majority of which have
never been through standard peer-review, and seems to bias the selection to the work of people
review:
• explicit and transparent methods are used;
• it is a piece of research following a standard set of stages;
• it is accountable, replicable and updateable’
• there is a requirement of user involvement to ensure reports are relevant and useful
(https://eppi.ioe.ac.uk/cms/Default.aspx?tabid=56).
From the information provided in the CfBT report, it is not clear that any of these criteria were
met.
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
with a personal commitment to the topic. The condition that some sources need to be from those
with “some form of university affiliation”, as it would seem to allow students at the very start of
their academic careers, but also individuals with only the most marginal connection with
academic research. Interestingly, the literature review includes no reference to the critical
literature on NLP (e.g., Witkowski, 2010). The rest of the report is dominated by ’24 teacher-led
action research case studies’ (p. 6), in which teachers explored the use of NLP in their
classrooms, following a short course. These case studies do not seem to follow any recognised
method for either action research (e.g., McNiff, 2013) or for the generation of case studies (e.g.,
Yin, 2009). Instead, they amount to little more than anecdotal reports of ‘positive impact’,
‘reduced misbehaviour’, and improved understanding of the ‘needs of pupils’. No measures are
given to support these findings, but the authors of this report were nonetheless able to state
confidently that “The evidence … clearly suggests that this project had a significant impact for
the teachers and the schools involved” (p. 26). It may be the case that these experiments led to
some improvements for students. It might also be the case that they caused harm. In the absence
of some objective measures, such claims are meaningless.
Brain Gym, or sometimes Educational Kinesiology, is a very popular commercial brain-based
programme, founded on the premise that learning problems are caused when different sections of
the brain and body do not work in a coordinated manner, thereby blocking a student’s ability to
learn. To overcome these learning blocks, 26 simple movements are prescribed that are designed
to improve the integration of specific brain functions with body movements. Students are led
through combinations of crawling, drawing, tracing symbols in the air, and yawning (the latter
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
action is claimed to improve eyesight; Dennison & Dennison, 1994). Lying behind Brain Gym’s
activities are three main theoretical hypotheses that have been borrowed and adapted from older
theories: neurological repatterning, cerebral dominance, and perceptual–motor training (ibid.).
Neurological repatterning is based on the idea that children develop in a linear manner, and that
they must acquire specific motor skills during different developmental stages. If the skills
associated with any of the developmental stages are missed, then neurological development is
hindered and learning abilities are limited (Crain, 2000). For example, an infant who walks
before crawling will miss a critical step in motor development, which could account for future
difficulties with more complex neurological processes, such as reading. The treatment for this
problem, therefore, is to teach the child to crawl, with the idea that this would repattern the
neurons, leaving the child neurologically intact and ready to acquire academic skills. Cerebral
dominance maintains that students who do not have a dominant hemisphere of the brain have
weaker cognitive abilities, specifically difficulties with reading (Howard-Jones, Pollard,
Blakemore, et al, 2007). The exercises of Brain Gym are intended to improve this hemispheric
control (Dennison, 2009). Finally, perceptual motor training traces specific learning problems to
the poor integration of visual, auditory and movement skills. So, teaching certain perceptual
skills will result in the improvement of learning.
None of the foundational principles, at least as they are interpreted in Brain Gym, have empirical
support (Hyatt, 2007). The American Academy of Pediatrics (1982) has repeatedly denounced
neurological repatterning, expressing serious concerns with the procedures, the claims of
successful interventions, and the concomitant lack of empirical evidence. Cummins’ (1988)
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
comprehensive analysis of the effectiveness of neurological repatterning found results supporting
its effectiveness come from a small number of poorly controlled studies, and that there was no
further evidence in its favour since that time (Ruhaak, & Cook, 2016). It seems likely that any
improvements observed in children following the programme are attributable to increased
activity levels and attention paid to them. The cerebral dominance hypothesis seems to be based
on a misunderstanding of the neuroscientific concept of modality, the fact that some parts of the
brain do seem to be more involved in specific activities and emotions (Eagleman, 2015).
However, it does not follow, as Brain Gym assumes, that individual parts of the brain control
different processes and movements. The relationship between the two hemispheres of the brain is
extremely complex, but nothing in the current understanding supports cerebral dominance
(Hausmann, 2017). Finally, despite its continued popularity in some quarters, the effectiveness of
perceptual motor training as an academic intervention has never been demonstrated (Kavale &
Forness, 1987; Ruhaak, & Cook, 2016).
Despite its unstable foundations, Brain Gym supporters continue to promote its methods, and
schools continue to include them in their curriculum (Tardif, Doudin, & Meylan, 2015). In
addition, academic papers continue to be produced claiming to support Brain Gym’s claims (e.g.,
Donczik and Bocker, 2009; and ‘A Chronology of Annotated Research Study Summaries in the
Field of Educational Kinesiology’; Brain Gym International, 2003). However, scrutiny of this
literature gives rise to some concerns. The most obvious is that hardly any of this literature is
published in peer-reviewed academic journals, and appears in the in-house ‘Brain Gym®
Journal’. Brain Gym International, (2003) explains this in terms of the mainstream scientific
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
community’s exclusive interest in studies that have been undertaken experimentally with control
groups and demonstrating statistical significance. This is not true, nor is the claim that scientific
journals will not publish research that has previously appeared in ‘Brain Gym® Journal’.
Ironically, many of the articles compiled to demonstrate the effectiveness of Brain Gym still
claim statistical significance and the use of experimental techniques (e.g., Donczik and Booker,
2009). In many of these cases, the problems seem to arise not from the scientific establishment’s
exclusionary practices, but from quite fundamental errors in methodology, such as
misinterpreting statistical significance, using of incomparable control groups, failing to account
for maturational effects.
By far the most researched neuromyth is learning styles, and academic interest into this subject
reflects its very widespread acceptance in many countries (cf. Dekker, Lee, Howard-Jones, et al,
2012). In fact, the term learning styles embraces a varied set of claims, inventories, and models
for assessment (Coffield, Moseley, Hall, et al, 2004), but each of these theories maintains that
people learn in qualitatively different ways, and that formal experiences can be tailored to the
individual learning style of the student. For example, a very common form of the theory
promotes the ‘VAK’ model in which some people learn best by observing (‘visual learners’),
some by listening (‘auditory learners’), and some by doing and moving (‘kinaesthetic learners’).
Learning styles theory also maintains that difficulties in school can often be traced to a mismatch
between the student’s learning style and the ways in which information is presented by the
teacher (ibid.).
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
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© Richard Bailey, 2017
The VAK version of learning styles offers an attractive alternative to more traditional approaches
to teaching, combining a scientifically appearing, but simple framework for learning with the
promise of addressing perennial problems of learning difficulties and lack of motivation. It
certainly seems to be the case that teachers are often inclined to accept its claims. A review of
studies from the UK, the Netherlands, Turkey, Greece, and China found that more than 90% of
teachers agreed that students learn better when they receive information tailored to their
preferred learning styles (Howard-Jones, 2014). Similar findings from studies with teachers and
trainee teachers in Portugal (Rato, Abreu, & Castro-Caldas, 2013), Latin America (Gleichgerrcht,
Lira Luttges, Salvarezza, et al, 2015), Turkey (Dündar, & Gündüz, 2016), and China (Pei,
Howard-Jones, Zhang, et al, 2015) suggest that learning styles have a firm foothold in
educational practice around the world.
These findings suggest that learning styles are generally accepted by both professional and the
general population, and the quantity of books, articles and websites of the subject might suggest
that the hypothesis at the heart of the theory - that matching teaching style to students’ learning
style - leads to improved learning, has been well studied, but that conclusion would be incorrect
(Rogowsky, Calhoun, & Tallal, 2014). In fact, there is no compelling evidence that matching
formal instruction to individual perceptual strengths and weaknesses is any more effective than
instruction, which is not multi-sensory specific (Rohrer, & Pashler, 2012). Teaching according to
an assumed preference may even cause harm, as learning is best promoted by taking students out
of their comfort zones, not keeping them in it (Coffield, Moseley, Hall, et al, 2004). One
reviewer of the claimed evidence wrote that “very few studies have even used an experimental
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
PLEASE REPRINT FOR EDUCATIONAL PURPOSES ONLY
© Richard Bailey, 2017
methodology capable of testing the validity of learning styles applied to education. Moreover, of
those that did use an appropriate method, several found results that flatly contradict the popular
meshing hypothesis” (Pashler, McDaniel, Rohrer, et al, 2008, p. 105). Almost all of the evidence
base claimed for learning styles is theoretical and descriptive in nature rather than empirical, and
rarely appears in peer-reviewed journals. The studies that do follow typical scientific procedures,
such as featuring a randomly assigned control group, do not support the learning styles
hypothesis (ibid.). Even researchers inclined to accept the existence of learning styles have been
unable to provide empirical support for the claims (Kozhevnikov, Evans, & Kosslyn, 2014).
Most of the pseudoscientific claims discussed here fall within the category of ‘bad science’
introduced in the Introduction to this chapter. Learning styles, and similar assessment methods,
are different, as the use of spurious cognitive assessment methods can be harmful to students,
since they can result in teachers erroneously labelling students as being of a certain ‘type’, and
providing a range of restricted resources that are appropriate to that type. Thus, they are ‘ugly
science’: in addition to a restriction of educational opportunities that is likely to follow from this
labelling process, and the detraction from the use of techniques which are demonstrably effective
(Willingham, Hughes, & Dobolyi, 2015), there is a real danger that students will internalise these
labels and think of themselves as certain types of learners who should limit themselves to the
diagnosed activities (Demos, 2004). Consequently, the intrusion of some of these
pseudoscientific practices into classrooms can waste a lot more than merely time and money;
they can harm students’ learning and development.
This chapter will appear in: Bailey, R.P., Tomporoski, P., Meussen R. and Schaeffer, S. (in
press). Physical Activity and Educational Achievement: Insights from exercise neuroscience.
London: Routledge.
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© Richard Bailey, 2017
The brain-based theories discussed in this section were selected because they all touch upon the
central concerns of this book, and as the chapters and the rest of this volume demonstrate, there
have been remarkable developments in the understanding of the relationships between physical
activity, the brain, and educational achievement in recent years. So, despite the different
limitations of these alternative theories, they share the same kernel of truth. The problem is that
they extrapolate far beyond the valid and reliable evidence base, or misunderstand the findings
and their implications. For example, several chapters in this volume demonstrate that cognitive
function benefits from cardiovascular fitness and physical activity (e.g., XXXX). But it does not
follow that the stylised movements of Brain Gym result in the activation of particular areas in the
brain. Likewise, it is almost certainly the case that some students prefer movement-based ways
of learning over others. It does not mean, however, that these preferences have any link to innate
differences in the brain, nor that matching those preferences with pedagogy will accelerate
learning.
It might be asked if the distinction between science and pseudoscience matters. Perhaps the
proliferation of neuromyths and other pseudoscientific ideas form a harmless tax on people’s
gullibility and scientific illiteracy? That might be true in some cases. Many worthless ideas
circulate, and with extraordinary speed thanks to social media (Pentland, 2014). If people wish to
take homeopathic remedies or vitamin tablets for minor ailments like colds, the effect is unlikely
to be nothing more than a placebo effect and interesting coloured urine (of course, if they take
these tablets instead of actual medicine, the costs could be much more serious). However, as has
been suggested earlier in this chapter, introducing pseudoscience into classrooms is rarely
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without harm. Educational systems have finite financial and time resources, and engagement
with learning styles inventories or Brain Gym movements usually means fewer opportunities to
participate in activities that are likely to prove more worthwhile. It is hardly surprising that many
of these ideas are couched in the language of neuroscience as they feed on a tendency to accept
almost any claim if it appears to be backed by neuroscience (Weisberg, Keil, Goodstein, et al,
2008). Allowing such ideas into the classroom gives them a credibility that undermines a
meaningful distinction between the hard-won evidence of scientific research and over-blown
claims of untested products.
So, untested, unregulated and unsupported scientific practices can be harmful. There are other
dangers, too, as outlined by the philosopher and biologist Massimo Pigliucci, who claimed that
debating and exposing pseudoscience is important for a number of reasons:
“The first is philosophical: demarcation is crucial to our pursuit of knowledge; its issues
go to the core of debates on epistemology and of the nature of truth and discovery. The
second reason is civic: our society spends billions of tax dollars on scientific research, so
it is important that we also have a good grasp of what constitutes money well spent in this
regard … Third, as an ethical matter, pseudoscience is not — contrary to popular belief
— merely a harmless pastime of the gullible; it often threatens people’s welfare,
sometimes fatally so.” (2013, unpaged)
There is high risk that some of these myths will propagate among teachers and then to students,
and it needs to be remembered that some of the consequences of these pseudoscientific ideas
harm children. Teaching students that they have a specific learning style, or that their poor scores
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are due to faulty integration between the hemispheres of their brains based on no valid or reliable
evidence, risks limiting their educational opportunities and damaging their long-term
achievements. It is known that many teachers wish to build on knowledge generated from
research in neuroscience (Pickering & Howard Jones, 2007). However, without an ability to tell
the difference between good, bad and ugly science, those teachers are vulnerable to become
victims of professionally marketed fads and fashions. The extremely widespread acceptance of
pseudoscientific beliefs among teachers (e.g., Dekker, Lee, Howard-Jones, et al, 2012) is
testament to this danger.
If the distinction between science and pseudoscience does matter, then it seems important to have
some way of telling the difference. This has proved to be a challenging task, and is one that
continues to generate debate among both theorists and practitioners. Some of the terms of this
debate are discussed in the next section.
The Demarcation Problem
The previous section has shown that practitioners are bombarded with claims about various
supposedly brain-based theories and products, and most of them are couched in impressive-
sounding language and the signs of science, such as brain images. So, it is often difficult to tell
the difference between those ideas that are based on real science and those that merely pretend to
be scientific. This latter group of ideas is sometimes called pseudoscience, because they
masquerade as science. Collins and Bailey (2013) offered an alternative terminology for theories
and practices that look superficially like science - “scienciness”, which they define as, “the
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illusion of scientific credibility and validity that provides a degree of authority to otherwise
dubious ideas. Scienciness is conveyed through, for example, esoteric language and complex
statistical representations, and supplemented by association with an apparently successful foreign
system” (p. 2). Scienciness is just a more graphic term for pseudoscience.
Although science has been defined in many ways, most people who have examined the subject
agree it is ultimately not a body of knowledge, but a way of establishing and developing a body
of knowledge (Shneider, 2009). The philosopher, Karl Popper hinted at this view when he
described science as a process of bold guessing, followed by rigorous testing. In other words, at
the heart of science is criticism - self-criticism and the criticism of others. Popper (1994) said:
“What we call scientific objectivity is nothing more than the fact that no scientific theory is
accepted as dogma, and that all theories are tentative and are open all the time to severe
criticism” (p. 160). Pseudoscientific theories claim to conform to the norms of science, but, when
judged impartially, the claims violate them (Koertge, 2013).
The challenge of telling the difference between science and pseudoscience is called the
demarcation problem (Popper, 1934). One difficulty confronting anyone reflecting on these
issues is that there are many different types of science (such as theoretical and applied),
concerned with many different sorts of objects (including people, animals, plants and minerals),
at different stages of disciplinary maturity (from emerging areas of research to well-established
sciences). Consider, for example, some of the types of research reported in recent Sport and
Exercise Sciences journals:
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◆ Randomised control trials of the effectiveness of physical activity interventions;
◆ Surveillance reports of sports participation around the world;
◆ Analysis of specific groups’ motivations to engage in exercise;
◆ Systematic literature reviews and meta-analyses of various, narrowly defined topics;
◆ Observational studies of sports coaches’ behaviours;
◆ Laboratory studies of oxygen uptake on a treadmill;
◆ Brain scans of skilled practice.
Research methods used in any multi-disciplinary field are likely to be diverse, since the methods
of each of the parent disciplines can potentially be used, and this variety will only be multiplied
when that field encompasses both theoretical and applied work, and populations ranging from
shortly after birth to death. In fact, the range of methods used by sport and exercise scientists is
even wider than that, since many methods regularly used have been imported from further afield.
Systematic reviewing has origins in agricultural studies of seeds and fertilisers. Cluster analysis
was first used by bacteriologists. And the detailed observational procedures used to track player
behaviour during a game or session were imported from ethologists’ studies of animals in the
wild.
Karl Popper is the philosopher most associated with the problem of demarcation, He argued that
a theory is scientific if it can be shown to be false. This is in contrast to the idea that science
operates through the generation of confirmations of theories, which had previously dominated
discussions of the scientific method (and sometimes, in various forms, to this day). Popper
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argued the relative power of positive and negative evidence is asymmetrical: no amount of
confirmations can demonstrate a theory’s value because it is always possible to find them; but a
single falsification, he claimed, can kill a theory dead. The scientist (or at least the good
scientist) does not search for evidence that seems to support a theory, but looks for ways in
which it might be found to be mistaken. In other words, genuinely scientific theories include
statements that could be shown to be false by empirical evidence; pseudoscientific theories do
not. Popper (1934) used his famous ‘Black Swan’ argument to force through the distinction
between the persuasive powers of positive and negative evidence, which is paraphrased below:
For thousands of years, Europeans had observed millions of white swans. Because of this,
they induced (generalized) the theory that ‘all swans are white’. However, exploration of
Australasia introduced Europeans to black swans. The theory that ‘all swans are white’
was dead.
Poppers' motto is that no matter how many observations are made which confirm a theory, there
is always the possibility that future falsifying observations refute it. The spirit of falsification
continues to extend to the scientific community, where the "friendly-hostile co-operation" of
scientists (Popper, 1994) is expressed through mechanisms like peer review of articles.
Falsification as the criterion of demarcation continues to be influential among scientists, but
philosophers have generally abandoned it as a sufficient standard for setting science apart from
pseudoscience. There have been various criticisms of Popper’s view, but the most damaging is
the ‘Quine-Duhem Problem’ (Hacking, 1999). This is based on the observation that when a
scientist tests a theory, it is not in isolation from other assumptions and hypotheses. So, what
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appear to be observations that falsify a theory might be some other factors. Popper modified his
theory in response to these criticisms, arguing that scientists should be explicit about both the
theory and any associated assumptions and hypotheses that might affect it. This is a stronger
position, since it means that the scientist is prepared to dictate more fully the theoretical and
experimental conditions necessary for proper testing. However, it does not adequately deal with
the Quine-Duhem Problem, since it will never be possible to remove with complicating variables
completely.
While philosophers of science have tended to reject Popper’s formal theory of falsifications,
most broadly endorse its central tenets, such as the central importance of a critical approach,
well-designed tests and a suspicion of an over-reliance on confirming evidence. However, some
philosophers have offered different theories of sciences. There is not enough room to review all
of these theories (see, example, Chambers, 1996; Monton, 2013), and that is not necessary for
present purposes. It is worth noting, however, that despite the sometimes-fractious debates
among philosophers, many philosophers would concur that, at least at the most general level,
certain basic elements cut across most or all scientific disciplines. Specifically, different
sciences, despite their diversity, are marked by (a) a willingness to root out error in one’s beliefs,
and (b) the implementation of procedural safeguards against confirmation bias - the deeply
ingrained tendency to seek out evidence consistent with one’s hypotheses and to deny, dismiss,
or distort evidence that is not (Lilienfeld, 2012). So, despite the evident differences between the
sciences, they all seem to share certain core characteristics, and pre-eminent among these is a
commitment to criticising and testing proposed ideas ruthlessly, and remove potential barriers to
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that criticism and testing. Moreover, there is a much greater degree of agreement about what
pseudoscience looks like (e.g., Koertge, 2013; Lilienfeld, Lynn, & Lohr, 2003).
Unfalsifiability - Popper’s early insights came from his observation that some theories are
apparently impossible to prove mistaken, whether because they do not make clear hypotheses
that could be tested, or that they interpret any criticism in terms of the malicious intent of the
critic. The mixture of practices, including mystical constructs like Jung’s personality theory,
suggests that the Action Types Approach (see Note 1) is difficult to falsify, or even measure.
Absence of self-correction - Despite the identification of flaws in their ideas, pseudoscientists
often keep faith in the original. Consider the case of Brain Gym as a paradigm example of this
phenomenon, in which every one of its foundational principles has been shown to be either false
or misinterpreted, but the programmes continue to be sold regardless.
Overuse of ad hoc immunising tactics designed to protect theories from refutation - It is common
for promoters of pseudoscience to add supplementary ideas to deflect criticism. An example of
this ploy is the claim by Carey, Churches, Hutchinson, et al (2010) that the critical responses to
the NLP are invalid due to “inaccurate application/interpretation of NLP techniques” (p. 12), and
that “Only a small number of papers, from the 1980s, contain formal research evidence that is
critical” (p. 12); the first claim might be true, if unlikely, the latter is simply false (cf. Witkowski,
2010).
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Absence of connectivity with other domains of knowledge - Many pseudoscientific ideas seem to
come from nowhere, and have little or no relationship with current scientific understanding of a
topic. As other chapters in this book demonstrate, there is now persuasive evidence that aerobic
exercise, classroom activity breaks and active play can enhance cognitive functioning, but none
of this research has been properly integrated into the theorising of Brain Gym, NLP or other self-
described brain-based methods.
Use of obscurantist language - Social media is littered with products prefaced with ‘neuro’,
‘psych’, ‘physio’, and using incomprehensible descriptions, clearly aspiring for some sort of
‘science’ legitimacy. The Myers-Briggs test tells people that they are ‘ENFJ’ (extraverted
intuitive feeling judging), ‘INTP’ (introverted intuitive thinking perceiving), or another of the 16
types drawn from the inventory (Barbuto, 1997). Or consider this quotation from the Brain Gym
teachers’ guide, which combines vague references to neurological language with factually
incorrect statements about learning:
“The Brain Gym Lengthening Activities help students to develop and reinforce those
neural pathways that enable them to make connections between what they already know
in the back of the brain and the ability to express and process that information in the front
of the brain … The front portion of the brain, especially the frontal lobe, is involved in
comprehension, motor control, and rational behaviours necessary for participation in
social situations. The Lengthening Activities have been found to relax those muscles and
tendons that tighten and shorten by brainstem reflex when we are in unfamiliar learning
situations.” (Dennison & Dennison, 1994, p16)
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Over-reliance on anecdotes and testimonials at the expense of systematic evidence - Two of the
most reliable markers for pseudoscience are the use of statements of support from satisfied
customers, and the absence of reference to actual science. Most of the websites discussed here
contain enthusiastic statements of support for their products. Although the ‘case studies’ in
Carey, Churches, Hutchinson, et al’s (2010) report on NLP offer no measures of improvement,
they are littered with comments like “this has been a life-changing experience” (p. 59), and “The
impact of the knowledge base has been immense. It has changed me as a person” (p. 94). To be
clear, such statements are not presented as testimonies by the report authors, but explicitly as
evidence for the effectiveness of NLP in schools (ibid., pp. 16-18).
Evasion of peer review - Pseudoscientific ideas are seldom presented for independent
assessment. The use of the Brain Gym® Journal, self-publications, and other in-house strategies
for disseminating generally low-quality information is an example of this, as is the use of student
essays and other unpublished, non-reviewed materials in Carey, Churches, Hutchinson, et al’s
(2010) review of the literature on NLP.
Contrast this with the scientific studies discussed elsewhere in this book. Figure 1 summarises
the most basic form of peer review.
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Figure 1: the basic peer review process
Emphasis on confirmation rather than refutation - Since it is almost always possible to find
positive evidence, no matter how implausible, it is quite a simple matter to compile
confirmations of ideas. If, for example, I am wedded to the idea that middle-aged male
academics have a uniquely appealing charm, I simply need to:
• Pay particular attention to any especially charming middle-aged male academics I
might come across as confirmatory instances;
• Either ignore, or preferably interpret, non-charming behaviour from middle-aged
academics, rather like the way TV audiences have apparently learned to admire the
ignorant and boorish behaviour of ‘talent show’ judges’!
The search strategy used in the report on the educational applications of NLP by Carey,
Churches, Hutchinson, et al (2010) results in a bias towards supportive findings. A more
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scientific approach would have compile a list of inclusive criteria before undertaking the search,
and perhaps invite potential critics to comment on these criteria. Such inclusive criteria would
probably not allow low-level resources to pass, such as student essays, and would insist on a
standard for admission considerably higher than “some form of university affiliation”.
Considered individually, these criteria are insufficient to indicate that a field is pseudoscientific
or has cause for concern. None is sufficient to indicate pseudoscience. Conclusive falsification,
as has been seen, is extremely difficult, and obscure language is hardly absent from scientific
journals. In fact, many of these characteristics could be identified in the work of reputable
scientists. The list also does not aim to show the necessary conditions for pseudoscience. The
field is too complex and varied to be reduced to simple clues. The philosopher Ludwig
Wittgenstein (1953) argued that some concepts do not have universally true features, but rather a
patchwork of related family resemblances that may or may not fit to each application. Perhaps
pseudoscience is one such concept; it is too fuzzy to succumb to a simple declination and
requires, instead, on-going discussion by theorists and practitioners about the nature of their
work and the types of evidence that ought to inform it.
Despite the variations of its forms and the sometimes inaccessibility of its methodologies,
science is ultimately a method of “arrogance control” (Tavris and Aronson, 2007). The scientific
method consists of a series of checks and balances that force scientists to doubt their most
cherished and strongly held assumptions. Some of the pseudoscientific claims discussed in this
chapter appear to be driven by the profit motive, but conversations with proponents of others
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make it clear that their commitments are often well-meaning. A recent online discussion
(personal communication) with the inventor of movement- and brain-based programme is
revealing:
“A: Could you please tell me about the evidence you have in support of this programme?
B: The thousands of children it has helped.
A: OK, but I meant, have you tested these benefits using scientific tests? For example,
did you use control groups?
B: I don’t have time for things like that! There are children in schools now who need [the
programme]
A: But I still don’t understand how you know it works. If you are relying on your own
observations, surely that is limited? After all, it is your programme. You developed it, and
have invested quite a lot of your own money in it. Aren’t you worried that your subjective
judgements could be unintentionally biased. You could be seeing what you want to see.
B: I’ve been working in schools for 30 years. I know what works! Anyway, the teachers
tell me about the benefits.
A: But these teachers invited you into their classrooms, didn’t they?
B: Yes, because they want the best for their children.
A: I have no doubt that is true. And I don’t doubt you are convinced of the value of [the
programme]. But what I am struggling with is the lack of objective measures. Without
some sort of non-subjective assessment, I can’t see how you can be so confident in your
claims.
B: All I can say is that I have seen [the programme] improve children’s performance. I
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have never seen a child fail with it. But I do intend to bring some researchers I’ve been
working with. Because you are right, we need the numbers.”
The social psychologist Timothy Wilson (2011) gathered evidence from studies measuring
people’s responses to programmes like those discussed above. His analysis shows how bad
human beings are at knowing why they reacted to situations as they did. They tend to impose
plausible explanations about the causes of those reactions, just as they do when trying to make
sense of others’ behaviours. This is especially true when they encounter novel situations, such as
a new educational intervention, and have nothing with which to compare it. In fact, the problem
of assessing effects of programmes is even worse. When people have gone through a programme
designed to help those for whom they care, there is a tendency for them to misremember how
things were before that programme began, therefore overestimating the effects of the
intervention. Wilson (2011) advocates a "don't ask, can't tell" policy - by not asking people how
much they benefited. Human beings are not very accurate at assessing the causes of their own
feelings, attitudes, behaviour” (ibid., p. 26). This advice does not dismiss the views of recipients
of programmes from the research process. It is just a suggestion that it is unwise to rely too much
on the recipients of an intervention to provide an accurate assessment of the nature and extent of
influence on their behavior or understanding. The various methods developed over the centuries
by science have the significant advantage purely because they aim to be non-subjective and non-
personal.
Conclusion
The American Nobel prize-winning physicist Richard Feynman (1974), in a speech at the
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Californian Institute of Technology, warned his audience of young science graduates about the
dangers off ‘cargo cult science’:
“In the South Seas there is a cargo cult of people. During the war they saw airplanes land
with lots of good materials, and they want the same thing to happen now. So they've
arranged to imitate things like runways, to put fires along the sides of the runways, to
make a wooden hut for a man to sit in, with two wooden pieces on his head like
headphones and bars of bamboo sticking out like antennas—he's the controller—and they
wait for the airplanes to land. They're doing everything right. The form is perfect. It looks
exactly the way it looked before. But it doesn't work. No airplanes land. So I call these
things cargo cult science, because they follow all the apparent precepts and forms of
scientific investigation, but they're missing something essential, because the planes don't
land.” (Ibid., p. 11)
Feynman’s point was that, while it might accord with human nature to engage in wishful
thinking, good scientists learn not to fool themselves. Feynman’s warning could well be applied
to the myriad ‘brain-based’ strategies that pervade current educational thinking. Whereas it is
commonly stated in such schemes that the brain is the most complex object in the universe, it is
ironic that this assumption is then ignored in proposing pedagogies based on simplistic analyses
of complex phenomena. The neurosciences are complex and the accurate transfer of research
findings to the classroom is often difficult (Devonshire and Dommett, 2010). As has been seen in
this chapter, the gap between neuroscience and education has enabled many misconceptions
about scientific findings to arise.
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Despite teachers’ enthusiasm for what neuroscience might bring to education (Serpati &
Loughan, 2012), there are currently few direct contributions that can be directly applied to the
classroom, and the collaborative effort between the two disciplines should be considered as a
long-term process (Goswami, & Szűcs, 2011). It has become commonplace in writing about the
application of neuroscientific ideas to stress the need to explore ways of bridging the gap
between scientists and practitioners (e.g., Howard-Jones, 2014), and there is little doubt that lack
of communication between these groups have contributed to current levels of misunderstanding.
While there is certainly a lot of truth in this account, there is also a danger that the way the
problem is phrased might undermine efforts to address it. Neuroscience is still mainly a
laboratory-based activity. Even with the best of intentions, extrapolations from the laboratory to
the classroom need to be made with considerable caution. The scientist-practitioner gap, as it is
often called in the literature (Cautin, 2011) assumes a clear disjunction between scientists, who
gather evidence, and practitioners - in this case, teachers) who implement practices, whether
based on that evidence or not. However, this dichotomy is both misleading and unhelpful. It is
misleading because the lack of an understanding of basic scientific knowledge on the part of
teachers should not be accepted as a given at a time of near-universal teacher education and
professional development (Townsend, 2016). Nor should it be accepted that scientists, as a
group, are unable to engage with teachers in meaningful terms (Goswami, 2006). That such
blurring of the boundaries between scientists and practitioners happens too-rarely does not mean
that the boundaries cannot be transgressed.
Two conceptually distinct dimensions are at play here. The first is ‘science/non-science’; the
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other is ‘research/practice’ (McFall, 1991). As Figure 2 shows, these dimensions generate four
quadrants:
Science
Non-science
Research
Scientific researcher
Non-scientific researcher
Practice
Scientific practitioner
Non-scientific practitioner
Figure 2: The dimensions of science/non-science, research, and practice
The difference between these distinctions and the standard scientist/practitioner gap is vital,
because the former implicitly challenges the presumption that teachers should be to recipients of
research. Instead, it hints at the need to much more fully involve teachers in the production and
application of science in education. This might mean the inclusion of neuroscience and
psychology into initial teacher training and professional development courses (Pickering &
Howard Jones, 2007). More important, perhaps, would be a proper introduction to the scientific
method, including ways of evaluating claims of scientific credibility. Teachers need to learn not
just how to administer the ideas and practices presented to them, but also to become thoughtful
and discerning consumers of proposed evidence (Lilienfeld, Ammirati, & David, 2012). In an era
of evidence-based practice, this seems unarguable, not least because teachers are often the
gatekeepers of new claims in the classroom.
The model offered above also acknowledges that not all research that seeks a place in classrooms
is scientific, a point that should be amply clear from the earlier discussions of pseudoscience.
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The widespread acceptance of pseudoscientific claims about the brain and educational practice is
serious cause for concern. The situation in education is of particular concern as it impacts on the
life opportunities of children. Experimenting with children’s lives without very good reasons,
and without a clear awareness of the potential benefits and costs is morally reprehensible, and is
justifiably forbidden in many contexts. It is not obvious why children should not be protected
from the endless stream of bad and ugly products and practices that continue to flood into
classrooms. Many of these ideas have not been shown to work; others have been shown not to
work. Yet they continue to find a place in classrooms around the world. This is not a call for the
end of new ideas in education. On the contrary, such work is the life-blood of evidence-based
practice. But it is a call for caution about what is permitted to impact on children’s learning and
well-being, especially when what is being offered has no basis in science.
In late 2015, a psychological study made news headlines by bluntly demonstrating the human
capacity to be misled by “pseudo-profound bullshit” (Pennycook, Cheyne, Barr, et al, 2015). The
authors, through a series of experiments, conclude that “some people are more receptive to this
type of bullshit and that detecting it is not merely a matter of indiscriminate skepticism but rather
a discernment of deceptive vagueness in otherwise impressive sounding claims” (p. 549).
Neuroscientific explanations are especially vulnerable to this tendency. Studies by Weisberg,
Keil, Goodstein, et al (2008) show that even people with some neuroscientific knowledge (e.g.,
people who followed an introductory cognitive neuroscience class) can be fooled by
neuroscientific explanations in the same way as laypeople. This reinforces the need for any
professional education for teachers in neuroscience to be accompanied with information about
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how to evaluate claims, how to spot the markers of pseudoscience, and how to make informed
judgements about whether and how to implement new ideas and practices in their classrooms. In
light of the time, energy and money that has already been lost due to the encroachment of
pseudoscience into schools, as well as the potential harm that some of these can have on
children’s education, this is both a moral and professional necessity.
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