Extracts from ‘Neuroscience and technology enhanced
learning’ published by Futurelab.
“Neuroscientists generally
believe that human learning, as in the formation of memory, occurs by changes
in these patterns of connectivity between neurons – or ‘synaptic plasticity’.
…. In education, of course, we think about learning in ways that extend well
beyond the concept of memory. …. For that reason alone, neuroscience cannot
offer anything like a complete story of learning in the classroom.”
This is not the
same as saying that we should ignore the increasing discoveries of
neuroscience! This report describes findings from neuroscience which may help
understand how better to facilitate learning in our schools.
Vive la difference! How neuroscience helps us understand the need for
differentiation and personalisation.
Hoeft et al 2008 describe “gender
differences in how individuals respond to video games”. Feedback also appears
to be age related. Van Duijvenvoorde 2008 suggests that older people are more
influenced by negative than positive feedback. Luna et al 2004 “shows how a
range of factors that are critical to successful self-regulated
learning (processing speed, voluntary response suppression,
and working memory) mature across different age groups”.
This insight may better inform our expectations of how children of different
ages can self-regulate their learning.
Digital technologies can
increase pupil engagement by catering for individual differences including
ability, gender and age.
Special needs can be
targeted. Kucian et al 2011 “used an educational game based on neuroscientific
understanding to demonstrate remediation of dyscalculia in terms of numerical
performance and brain function”. Butterworth and Laurillard 2010 suggest that
using digital technology to help with dyspraxia can:
- provide easily-accessed and unsupervised
repeated practice
- be age-independent
- be sensitive to individual needs
- be meaningful by linking the physical to
the abstract, “such as when a learner ‘zooms into’ a 1–10 number line to
discover decimal numbers”
- be unthreatening
- offer feedback in an “endlessly patient fashion”.
But personalisation can go
further than this. “Technology can adapt dynamically to the changing needs of
the learner based on an automatic assessment of their responses.” In Graphogame,
a game which teaches children to associate graphemes with phonemes, “online
algorithms analyze a child’s performance and rewrite the lesson plans ‘on the
fly’ depending on which specific confusions the learner shows.”
If a picture says a thousand words … Or, two senses are better than one.
Illustrating text enhances
memory (Pavio and Csapo 1973). Brain scan experiments (Beauchamp et al 2004)
suggest that multimodal stimuli produce more brain activity than unimodal
although the “effectiveness of multimodal presentation as a memory/ learning
strategy appears to rely on whether it encourages processing related to
educational objectives.” (Dubois and Vial 2000)
“Adding auditory cues to a
virtual reality environment (comparing unimodal with multimodal) increased
activation in the hippocampus, a region strongly
associated with memory.”
(Andreano et al 2009)
Neuroscience also suggests
that learners should also be encouraged to touch things. “Object recognition by
touch and vision activate several overlapping and closely-related brain regions;”
again this leads to enhanced brain activity.
Collaborative learning: two heads are better than one too.
“Technology is
providing new opportunities to share ideas”.
Dumas et al 2010 found that “several aspects of social interaction that
may support collaborative learning, such as interactional synchrony,
anticipation of other’s actions and co-regulation of turn-taking, are
associated with neural synchronisation between collaborators’ brains as measured by EEG.”
Other
researchers (King-Casas et al 2005, Miller 2005, Boudreau et al 2009 show how trust
between potential collaborators develops through reciprocity and how different
contexts engender different types of trust.
Collaboration may
also enhance creativity by reducing the tendency to fixate on one’s own ideas
according to neuroscientific evidence from Fink et al 2010.
Do those brain training things really work?
There is “accumulating
evidence” that video games enhance some cognitive skills. However, computer
based ‘brain training’ does not seem to transfer to everyday learning. But Jaggi
et al 2008 found that “when young adults undertook a 19-day computer-based
training program that focused on developing working memory for 30 minutes a
day, it was found that not only their working memory, but also their …ability
to solve problems in new situations.”
Sleep deprivation: the dark side of technology
Technology is
ubiquitous and pervasive and this may pose a problem for learning. “Sleep plays an important role in memory, so ‘when’ we
learn influences ‘how well’ we learn, with better recall following a period
asleep than after the same period awake. Since technology now makes it easier for
us search out, learn, communicate and apply knowledge all day and all night,
this access can impact negatively on our sleep. For example, hormonal
developmental influences produce a phase delay in the circadian timing
mechanism of teenagers, but the use of mobile technology has also been shown to
contribute to their sleep loss [Van den Bulck 2004]. A recent study in the US
You can access the full
report here.
References
Andreano, J., et al., 2009. Auditory Cues
Increase the Hippocampal Response to Unimodal Virtual Reality.
Cyberpsychology & Behavior, 12(3):
p. 309-313.].
Beauchamp, M.S., et al. 2004, Integration of
auditory and visual information about objects in superior temporal sulcus.
Neuron 41 (5): p. 809-823
Boudreau, C., McCubbins, M.D. and Coulson, S. 2009. Knowing when to trust others: An ERP study of decision making after
receiving information from unknown people. Social Cognitive and Affective
Neuroscience, 4(1): p. 23-34
Butterworth, B. and Laurillard, D. 2010 Low numeracy and dyscalculia: identification and intervention. ZDM 42(6): p. 527-539.
Calamaro, C.J., T.B.A. Mason, and S.J. Ratcliffe, 2009.Adolescents Living the 24/7 Lifestyle: Effects of Caffeine and
Technology on Sleep Duration and Daytime Functioning. Pediatrics, 123(6): p. E1005-E1010.]
Dubois, M. and Vial, I. 2000 Multimedia design: the effects of relating multimodal information. Journal
of Computer Assisted Learning 16(2):
p. 157-165
Dumas, G., et al., 2010 Inter-Brain
Synchronization during Social Interaction. PLoS ONE 5(8)
Fink, A., et al., 2010. Enhancing
creativity by means of cognitive stimulation: Evidence from an fMRI study.
Neuroimage, 52(4): p. 1687-1695
Hoeft, F., et al., 2008. Gender
differences in the mesocorticolimbic system during computer game-play.
Journal of Psychiatric Research, 42:
p. 253-258
Jaeggi, S.M., et al., 2008. Improving fluid
intelligence with training on working memory. Proceedings of the National Academy
of Sciences (USA
King-Casas, B., et al., 2005.Getting to know
you: Reputation and trust in a two-person economic exchange. Science, 308(5718): p. 78-83
Kucian, K., et al., 2011 in press Mental number line training in children with
developmental dyscalculia. Neuroimage. Corrected Proof.
Luna, B., et al., 2004. Maturation of
cognitive processes from late childhood to adulthood. Child Development, 75(5): p1357-1372
Miller, G., 2005 Neuroscience - Economic game
shows how the brain builds trust. Science 308(5718): p. 36-36
Paivio, A. and Csapo, K. 1973. Picture
superiority in free recall: imagery or dual coding? Cognitive Psychology, 5:
p. 176-206
Van den Bulck, J., 2004. Television
viewing, computer game playing, internet use
and self-reported time to bed and time out of bed in
secondary-school children. Sleep, 27 p. 101-104
van Duijvenvoorde, A.C.K., et al., 2008 Evaluating the
negative or valuing the positive? Neural mechanisms supporting feedback-based
learning across development. Journal of Neuroscience 28(38): p. 9495-9503
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