1. Dr. Oliver Hulme Computational models and Education How computational models of development could apply to educational practiceEducation and Neuroscience workshop Oct 2008

2. Computational models and Education Computational modeling of cognitive development offers a novel framework for thinking abouthowa child does something (counts, reads, learns etc) Models make concrete predictions about developmental processes and therefore could be used to predict the outcome of educational interventionsThis provides opportunity for formally optimising educational interventions To delineate how, I will explore a (crude) comparison between medicine and educational neuroscience 3. Medical and Education? Commentators have highlighted the abstract similarity between medicine and education (Schlagger, Fischer etc) Biology Medical Interventions EducationalInterventions MedicineEducational neuroscience 4. Medical and Education? Biology Medical Interventions EducationalInterventions Given that Medicine has translated biological knowledge into real world interventions that workHow can Educational Neuroscience adapt this paradigm?Developmental modelling could be critical for this translation 5. Medical ParadigmMedicine predominantly intervenes through pharmacology Problem:Millions of candidate drugs but cannot clinically test all due to ethical and resource constraintsSolution:Filter out poor drugs + clinically test few that are most likely to work Candidate drugsLead compound Clinical trialMarket 6. Drug discovery by screening Computationally model the potential efficacy of candidates to identify lead compounds (virtual high throughput screening) Pre-selects drugs for clinical testing ScreeningCandidates Lead compound 7. Educational Paradigm? Education intervenes through technology and teaching Problem:Millions of potential interventions but cannot test all due to ethical and resource constraints Solution:Filter out poor interventions + only empirically test select few that are most likely to work Candidates interventionsLead intervention Pedagogical trialSchools 8. Concrete examples? Suppose we are trying to optimise reading performance for phonological dyslexia through educational intervention Problem: The space of possible interventions is infinite How to define reading performance Solution: Test subspaces (i.e. a limited set of dimensions) Operationalise reading performance with an established index 9. For example Operationalise reading performance by word recognition accuracy Select subspace of interventions involving simultaneous presentation of graphemes and phonemes and select 3 variables to manipulate Even this subspace contains a large number of candidate interventions Intervention subspace RewardRepetition rateAge 10. Candidate Interventions? Screen: Use computational models of development to screen the potential efficacy of each intervention on word recognition accuracy lead interventions ( eg Predicted optimum is age 12, repetition rate = 10, reward = 3 hedons ) Models direct us to parts of intervention space thatpredict educational best results ScreeningRewardRepetition rateAge 11. Pedagogical trials Only empirically test the efficacy of the lead interventions in ecologically valid settings Select educational interventions based on evidence 12. Advantages of using models to screen Can explore educational interventions which may be unethical to pilot on humans Can explore how multiple variables interact to impact on educational performance Can test parts of intervention space that would be appear too stupid to test in real life and opens up possibility of unexpected results Can test effects of interventions on whole developmental trajectory not just a discrete timespans 13. Open questions Framework applies to any type of computational model. Are connectionist models suitable for this implementation? Given that connectionist modelsare not intended to be neural models, but rather cognitive information processing models (Mareschal and Thomas 2007) The question is whether they are sufficiently grounded in biology to yield the accuracy required for predicting the outcomes of educational intervention 14. 15. ProblemsHow to map from model to reality How generalisable are the abstract tasks the model performs Difficulty of mapping existing interventions onto model parameters and vice versa 16. Dr. Oliver Hulme Plan 17. Dr. Oliver Hulme Plan What will the computational guys think What will the educators think What will the neuroscience guys think 18. Dr. Oliver Hulme TitleBiology Medical Interventions EducationalInterventions 19. Dr. Oliver Hulme TitleB Biology Medical Interventions EducationalInterventions 20. Dr. Oliver Hulme TitleB Biology Medical Interventions EducationalInterventions 21. Dr. Oliver Hulme Format 22. Most developmental psychologists describewhatchildren can do nothowthey they do it Knowing how a child does something, count, read, reason, offers the opportunity for principled intervention to improve or remediate that faculty. This would be the long term aim of educational neuroscience, having a physical theory of childrens development, and its interaction with educational interventions. Through these models one could facilitate optimal trajectories for each child. 23. Computational Modelling

A standard in the physical sciences

They are tools for exploring causal mechanisms of development

Can track HOW learning mechanisms interact with the characteristics of the environment to produce observed behaviors

Equally they would be tools for exploring the causal mechanisms of educational intervention and child development. This opens up the space of possible interventions and allows one more efficiently to identify subspaces which offer optimal developmental trajectories. How do the learning mechanisms interact with the characteristics of the educational environment to produce observable educational outcomes. 24. Computational Modelling

Of course, all models involve approximations!

Making the right approximation depends on the nature of the target problem and the of our understanding of the problem.

This involves collaboration between the psychologist, pedagogues, pedagogists, computational neuroscientists, 25. Building a model is NOT the same as building a baby! " The art of model building is the exclusion of real but irrelevant parts of the problem, and entails hazards for the builder and the reader. The builder may leave out something genuinely relevant; the reader, armed with too sophisticated an experimental probe may take literally a schematized model whose main aim is to be a demonstration of possibility." The question is whether in designing complex interventions the accuracy of the models trajectory may depend on what is left out.Models are tools for reasoning 26. Connectionist Models

Cognitive models loosely based on neural information processing

Develop internal representation as part of learning

Nottabula rasasystems.

I want to relate the mechanisms of neural information processing to behaviors characteristic of cognition 27. An illustrative example The What and Where of infant object-directed behaviors

Some old stuff

Some new stuff

Some future stuff

28. Dr. Oliver Hulme Plan 29. Dr. Oliver Hulme Plan 30. Dr. Oliver Hulme Plan Emphasis is on interacting with the environment. Education is an environmental intervention and therefore these models are suited to testing different interventions without ethical concerns of experimenting with a childs developmental trajectory. 31. Dr. Oliver Hulme Plan 32. Dr. Oliver Hulme Plan Full developmental model should also respond in the same way as a normal child to environmental interventions such as education. 33. Dr. Oliver Hulme Plan 34. Dr. Oliver Hulme Plan 35. Dr. Oliver Hulme Plan What are the parameters of an intervention? Reward schedule, magnitude, valence, frequency Optimal stage in developmental trajectory Longitudinal frequency? Personalised developmental models? Given a set of data pertaining to the infants pscyhology, set up a individualised model, against which one can test your interventions for a full blown individualised learning scheme Model full classrooms? Macroscopic forecast modelling of educational policy? 36. Dr. Oliver Hulme Plan How does it change now? What will it change in 5 years time? In 25 years time 37. Dr. Oliver Hulme Plan Review of Posners book by Bradley Schlaggar 38. Dr. Oliver Hulme Plan Kurt Fischer and others in the 1 stissue of MBE highlight the analogy between MBE and medicine, both using knowledge to inform practice.Medical applications of biological knowledgerequire independent empirical tests. Educational applications of biological knowledge also require independent empirical tests. Neuroscience and modelling of neuroscience data require judicious interpretation followed up by research that tests their application to the classroom