The Blue DOT 14 - Multidisciplinary Science & Evidence For Education

How Learning Essentially
OPINION
Changes the Brain and Why
this is a Good Thing
NIENKE VAN ATTEVELDT, CO-CHAIR, ISEE ASSESSMENT
Nienke van Atteveldt received
her PhD (cum laude) in cognitive
neuroscience from Maastricht
University in 2006. After diverse
postdoctoral research positions, e.g.
at Columbia University in New York
(2008-2011), she currently works as
Full Professor at the Vrije Universiteit
in Amsterdam where she leads the
Lab of Learning (www.laboflearning.
com). Her lab investigates the
developmental interplay between
students’ academic self-concept,
their functional brain networks (e.g.
for error and feedback processing),
and their learning trajectories and
well-being in school. Moreover,
they investigate how neuroscience
interacts with society, and how
we can optimize the educational
value of developmental cognitive
neuroscience research.
One important feature of
learning is that it changes
the brain. Whenever a
child (or an adult) learns
something new, some slight changes
occur in the chemical and physical
properties within the responsible
neural networks. Which changes occur
exactly depends on which neural networks
are being used. Connections between
neurons that are used a lot become
stronger and faster, and this is how we
learn. Following from this, teaching can
be seen as evoking such changes in the
brain. Now, while working in the
interdisciplinary team of UNESCO
MGIEP’s International Science
and Evidence based Education
Assessment (Duraiappah et al.,
2021), I have come to realise
that this feature of learning – its
material basis if you will – is not
as straightforward as I assumed
with my neuroscience-mindset.
This is also called brain plasticity,
as the brain’s organisation is not
fixed but malleable. In fact, framing
learning in this way can be perceived as
concerning, and this makes the dialogue
between educational neuroscientists and
the ‘critical neuroscience’ perspective
extremely important. In this article, I will
try to explain how understanding the
neuroscience of learning can be useful for
teachers and learners, either directly or
more indirectly, and I hope to take away
some misunderstandings, to facilitate this
constructive dialogue.
A clear example of how learning changes
the brain comes from the work of Stan
Dehaene and colleagues on how learning
to read transforms the brain. By comparing the brains of literate
and illiterate people, they showed how profoundly the brain
changes with reading instruction, both in visual and in languagerelated
neural mechanisms (Dehaene et al., 2015). A relevant
question is how such insights can be used to improve learning and
teaching, and foster child development towards flourishing.
A main challenge is that the conditions
under which most neuroscience studies
take place are not naturalistic, but rather,
situated in artificial laboratory environments
and tightly controlled to measure an
isolated process.
An example of neuroscience studies useful for education
are neuroimaging studies that show a better prediction
of learning difficulties, and of which treatment is effective
for whom, over and above behavioural indicators (Gabrieli,
2016). Moreover, neuroscience can contribute to our knowledge
about what are optimal learning conditions, for example in terms
of sleep, nutrition, etcetera (Thomas et al., 2020). More indirectly,
insights in how the brain learns and develops can influence beliefs
and attitudes. For example, a better understanding of protracted
adolescent brain development may stimulate teachers to provide
more guidance with planning or simply to be more patient and
understanding. Similarly, a better understanding of individual
differences (i.e., diversity) and learning disabilities may reduce
stereotypes and negative attitudes.
Clearly, there are also many challenges. A main challenge
is that the conditions under which most neuroscience
studies take place are not naturalistic, but rather,
situated in artificial laboratory environments and tightly
controlled to measure an isolated process. In other words,
most studies suffer from low ‘ecological validity’, making it hard
to translate the findings to real-life learning situations. Different
approaches are being taken to include more realistic contexts in
neuroscience studies (van Atteveldt et al., 2018). For example,
developments in portable neuroimaging devices, such as mobile
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