Centre for Educational Neuroscience

1

• Centre for Educational Neuroscience
• Workshop
• Friday March 6th
• www.educationalneuroscience.org.uk

2
WELCOME TO THE CENTRE FOR EDUCATIONAL NEUROSCIENCE
WORKSHOP

• TODAYS AIMS
• TO COME UP WITH TWO TYPES OF PROJECT FOR EACH
  THEME
• Urgent and feasible
• Speculative/blue sky
• To help you, we will offer a brief presentation
  of the themes, and, after lunch, a presentation
  by Pekka Räsänen, from the Niilo Maki Institute
  in Finland, which has been combining education
  with neuroscience since 1990, and may offer some
  instructive examples of whats possible here, and
  what is not really feasible.

3
Language DevelopmentJulie Dockrell, Jackie
Masterson, Matthew Saxton (IOE)Michael Thomas
(Birkbeck)Chris Donlan (UCL)
4
Strategic Objectives (1)

• To provide a better understanding of the ways in
  which the brain processes language throughout
  development, especially for those learners with
  specific language difficulties.

5
Strategic Objectives (2)

• To identify (early) differences in processing of
  language in order to trigger intervention.

6
Strategic Objectives (3)

• To identify the ways in which children naturally
  can overcome language-processing obstacles, and
  to evaluate the extent to which these changes
  result from compensation in brain activity

7
Strategic Objectives (4)

• To assess whether oral and written language
  difficulties form distinct clusters of cognitive
  deficits or are best understood as a reflecting a
  unitary continuum of cognitive difficulty

8
Strategic Objectives (5)

• To use these findings to create interventions
  for language deficits, and to evaluate their
  impact not only on attainment, but on brain
  function.

9
General Impact

• Classroom practice Developing teachers
  understanding of language learning processes and
  atypical developmental trajectories, so as to
  enhance the design of learning environments.
• Teacher involvement in research Collaborative
  development of language-specific
  educationally-relevant research agenda and
  evaluation of outcomes

10
Mathematical Development

• Prevalence of low numeracy (year 7 level at end
  of primary school) is about 6
• Mathematical development is very important in the
  life of individuals
• Low numeracy poor employment prospects
• Low numeracy Lifetime loss of 110,000 in
  earnings
• Low numeracy greater likelihood of mental and
  physical illness
• Low numeracy more truancy, more exclusion from
  school
• Low numeracy greater likelihood of imprisonment
• Mathematical development is very important for
  the nation
• Cost of lost taxes, additional educational
  support, social problems
• 2.4 billion per year

11
What we think we know

• Neuroscience
• Brain network for simple number processing and
  arithmetic
• Numerical abilities and disabilities are
  partially heritable
• Cognitive development
• Broad stages
• But individual variation
• Education
• Numeracy strategy hasnt made much difference to
  lowest attainers

12
Questions

• What are the causes of low numeracy?
• Environmental, neurological, educational,
  cognitive, genetic?
• How do these factors interact?
• When does it start to go wrong?
• How can we assess for the causes in each child?
• How can we design programmes to help each
  individual with low numeracy?

13
Conceptual Development

• Centre For Educational Neuroscience
• Workshop, March 6th, 2009

14
What are concept?

• Use simple definition from Murphy (2002)
• Categories are structures in the world
• Concepts are the mental representations of
  structures in the world
• Concepts organise our experiences and underlie
  generalisation

15
Different Types of Concepts

• 1. Organisational Concepts
• Taxonomies
• Ad hoc concepts
• Script-based concept
• Culturally specific (e.g., Medin)
• Evident from at least 2-years-old

16
Different Types of Concepts

• 2.Theory based concepts
• Theory-theory (Keil, Medin, Carey)
• Causal Beliefs (Gopnik)
• Biological Theory
• Physical Theories
• Present from 3-years-old

17
Conceptual Development

• Vast literature
• Bruner, Vygotsky, Piaget - stages of conceptual
  development
• Mandler - emerging taxonomic concepts
• Keil, Carey - emergence of Biological theories
• Vosniadou - world models

18
The Neuroscience of Concepts

• Ashby - Multiple category learning systems
• Some imaging evidence of complex concept
  acquisition (e.g., relational concepts,
  scientific reasoning Bunge, 2005)
• Almost no developmental work

19
Computational Approaches

• Every approach has tried its hand
• Connectionist models of oranisational concepts
  (taxonomic concepts)
• Connectionist models of Theory Theory concepts
  (Rogers McClelland, 2001)
• Bayes net models causal reasoning
• Bayesian account of domain structure
  learning(Tennebaum, 2008)

20
Potential Aims

• To seek a neural computational account of
  learning in complex conceptual domains typical of
  science education
• To identify the emerging functional neural
  systems that underlie childrens causal and
  taxonomic conceptual reasoning
• To trace how the emerging neural conceptual
  learning systems impact on the delivery of new
  concepts in the classroom

21
Possible Example Questions

• Science Education
• a) what are the characteristics of
  informally-derived concepts at a neural or
  organisational level that render them more robust
  than those acquired formally or symbolically via
  instruction alone?
• b) what are the additional effects of dialogue
  around concrete activities that lead to greater
  and more robust conceptual change than experience
  alone?
• c) what are the processes of change that underlie
  the generalisation and extension of concepts to
  novel materials?

22
Computational modelling

• Dr. Michael Thomas
• Birkbeck College

23
Computational modelling

• Illustrative problem from language development
• 40-60 of pre-schoolers identified for language
  delay will resolve language difficulties by
  school entry
• Why do some language delays resolve?
• Target intervention to children with most
  persistent delays
• How can these children be identified early on?
• What factors influence how delay resolves?

24
Language development
Neuro-computational parameters
Quality of environment
Language system
Teaching
Brain systems
Genes
Family
Learning and development
25
Development of inflectional morphology
Environmental variability (e.g., socio-economic
status)
T A L K ED
influences
influences
T A L K
Genetic variability (polygenic model)
26
Population modelling (n1000)
Time 1
27
Results

• Early diagnosed delay resolves in 66 of
  simulated cases why?

28
(No Transcript)
29
(No Transcript)
30
(No Transcript)
31
(No Transcript)
32
Mechanisms for delay

• What mechanistic differences discriminate between
  the groups?

33
Extending this work

• Predict tests at Time 1 to discriminate later
  delay types
• Test interventions
• Tailored to different delay types
• To optimise progression of children of different
  abilities
• Implemented models are powerful tools
• Combine principles of neuroscience with domains
  of education

Brain systems, learning mechanisms
Educational practices
Psychological data
Modelling
34
Effects of distraction and load on performance in
educational settings

• Nilli Lavie and Sophie Forster

35
Project plan

• Use our new behavioural measure of entirely
  irrelevant distraction (Forster Lavie, 2007
  2008) under varied levels of attentional load
• 1) Assess correlation with childhood ADHD
• For children establish a clear relationship
  between childhood ADHD and distraction during
  task performance
• For adults ask whether childhood ADHD can
  predict behavioural distraction in adulthood
  (pilot data promising!)
• 2) Can our distraction measure predict
  educational performance at school and in further
  education (promising pilot data with respect to
  Univ. grades)
• 3) Ask whether perceptual visual load reduces
  irrelevant distraction for school children (we
  know it does for adults) assess whether any load
  modulation of distraction can extend to ADHD (in
  children and adults)

36
4) Longer term aim (though also feasible now)

• If load modulates distraction for school children
  including those with ADHD design homework
  material with higher visual load and assess the
  effects on distraction and educational
  performance (reading comprehension, math sums)

37
Why Our new measure

• Use our new behavioural measure of entirely
  irrelevant distraction (Forster Lavie, 2007
  2008) under varied levels of attentional load

75 of trials
25of trials
Distractor absent
Distractor present
More akin to irrelevant distraction in
educational settings and daily life and therefore
more likely to correlate with childhood ADHD
38
Why Aim 1

• Aim 1) Assess correlation with childhood ADHD
• For children establish a clear relationship of
  childhood ADHD and distraction during task
  performance
• Previous ADHD research assessed distraction
  through response competition and Stroop-like
  effects results are mixed, and the distractors
  are task-relevant
• (clearer results found for irrelevant distraction
  in daily life settings e.g. in the zoo).
• For adults ask whether childhood ADHD can
  predict behavioural distraction in adulthood this
  clarifies better the extent of ADHD recovery

39
Why Aim 2

• Aim 2) Can our distraction measure predict
  educational performance at school and in further
  education (promising pilot data with respect to
  Univ. grades)
• Relate distractibility to educational performance
  Scientifically- important for the understanding
  of the relationship of attention and education,
• Education- once a critical determinant of
  learning and education is identified (i.e. level
  of distraction) this has implications for
  improving educational settings (e.g. minimising
  distraction)

40
Why Aim 3

• Aim 3) Ask whether perceptual visual load reduces
  irrelevant distraction for school children assess
  whether any load modulation of irrelevant
  distraction can extend to ADHD (in children and
  adults)
• Scientifically important for understanding
  attention effects on irrelevant distraction
  inc. in ADHD
• Education implications identifying visual load
  as a factor that can improve educational task
  performance (by minimising distraction) including
  for children with ADHD

41
Why Aim 4 (longer term or now)

• Aim 4) If load modulates irrelevant distraction
  for school children including those with ADHD-
  design homework material with higher visual load
  and assess the effects on distraction and
  educational performance (reading comprehension,
  math sums)
• Improve learning/education

42
resources

• 3 years project grant with one postdoc for aims
  1-3
• Research council ESRC

43
Social Development
Social Development Catherine Jones

• Catherine Jones

44
(No Transcript)
45
1. Early-years measures
46
Behavioural

• Looking preference
• Eye tracking
• Joint attention
• Observational assessments

Klin Jones (2008)
47
EEG

• Eye gaze
• Face processing
• Biological motion
• Joint attention

Elsabbagh et al (2009)
48
Early-years measures

• Associations between behavioural and imaging
  assessments
• Predicting later social functioning
• Measuring a developmental trajectory

49
2. Neuroimaging of key social cognitive processes
50
Mental state understanding

• Mental state animations
• False belief stories
• Communicative intent
• e.g. irony

Moriguchi et al (2007)
51
Neuroimaging of key social cognitive processes

• Associations between neural structure or
  functional activation with measures of social
  functioning (e.g. self/other ratings of social
  behaviour)
• Individual differences in developmental
  trajectory of structural or functional neural
  maturation. What are the implications?

52
3. Linking academic achievement to social
cognition and behaviour
53
Reading comprehension in ASD
38 of sample (n100) with a RC dip


r .296 p .003
54
Emotional Development

• Overall aims
• 1) To understand how emotion and cognition
  interact to produce a better learning
  environment.
• 2) To understand how emotion, emotion regulation,
  awareness of emotion develops over
  childhood/adolescence.

55
1) Emotion and Learning

• Basic research Emotion effects on e.g. memory,
  attention, in typically and atypically developing
  children.
• Applied Research How emotion affects learning
  environment, how emotional state can be monitored
  communicated to teacher.

56
2) Emotional Development

• Emotion experience, its regulation, and emotional
  awareness can be measured using neuroimaging.
• Neural areas are developing across childhood /
  adolescence.
• Track development across diff popns.
• Tailor emotional literacy programs to stage of
  emotional development.