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Computational approaches to learning – The educational perspective Diana Laurillard Institute of Education

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Computational approaches to learning – The educational perspective

Diana LaurillardInstitute of Education

Interdisciplinary relationships

Learner and

teacher activity

Learner model

Teacher model

Educational research

Technology enhanced learning

Learning theory

Pedagogic theory

Developmental psychology

Models of learning

Models of teaching

ComputationalModelling

Neuro-scientific

models of cognitive activity

Neuroscience

Cognitive

acts

Are there differences between Learning and Development?

Timescale Reversibility Age of onset

Rate Passive or Active?

Domain general

vs. specific

Underlying mechanisms

Type of info processed

Inductive method

LearningQuick

One shotMore

reversible (forgetting)

Later in life

Episodic?

Can be increased through practice

Passive internalisat

ion

Specific to task

Strengthen synapses

within architectures?

Experiences of an

individual

Search hypothesis

space given experience

DevelopmentSlow

Several years

Less reversible

Earlier in life

Cannot be accelerated

Active exploration

Global across

domains

Morphological changes of

neural architectures?

Experiences common

to all members of

species

Alter / enrich hypothesis

space

But learning also includes ‘active exploration’, and works across domains.Certainly reversible, but it’s worse than ‘forgetting’.CM ‘characterises learning as the process of change of structures in the brain’ – but what forms does ‘mis-learning’ take?

Notes from the SEN classroom

Teacher field notesResearcher interpretation of learner model

Researcher interpretation of teacher model

Interdisciplinary relationships

Learner and

teacher activity

Learner model

Teacher model

Educational research

Technology enhanced learning

Learning theory

Pedagogic theory

Developmental psychology

Models of learning

Models of teaching

ComputationalModelling

Neuro-scientific

models of cognitive activity

Neuroscience

Cognitive

acts

Siegler, Karmiloff-Smith, Lave, Resnick,

Engestrom

I tried asking him to count from 45 up. He got stuck at 49 and was unable to continue.

I asked him to go back to 5 and count up. He was then able to get from 9 to 10.

Next he counted across the decades from the 40s to the 70s. He was then able to return to the tape measure and continue up to 160.

Has representations of the number line in terms of units and 10’s, but not integrated as a single sequence

Piaget – construction,

Vygotsky – social practice

Generation of alternative incorrect representations of the number line? – models of not learning?

Recognise nature of misconception?Generate appropriate sequence of sub-tasks?

Facilitate learner constructions.Decompose the task to a component problem.Rebuild the task from the components he has.

Activate the IPS?Activate a dysfunctional network?Build the network across brain areas?

From physical to digital manipulables

Program-defined task for building across 10- learner-specific sequence of tasks- intrinsic feedback on action in relation to goal- no focus on counting- learner model based on accuracy and RTs- teacher model is rule set based on SEN practice, theory- evidence of gradual shift from counting to recognition in response to individualised feedback and sequence

Program-defined task - no learner-specific sequence- random tasks- right/wrong feedback- confusing representations

Interdisciplinary relationships

Learner model

Teacher model

Learning theory

Pedagogic theory

Models of learning

Models of teaching

Which learner activities would be productive for collaboration?Categorisation? Representation, v, s, p? Interpretation? Generalisation?

Which studies yield behavioural data or learning models we can use for diagnosis, and hypotheses we can test?

What kinds of studies would yield data that could generate learning models, and hypotheses CM can test?