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Studying the factors that influence how people generalise what they have learned to new contexts and situations. Basic research in this field provides guidelines on best to optimise generalisation of learned skills and knowledge.

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Competitive advantage

  • Extensive body of basic research on generalisation provides the scientific basis for improved training methods to optimise generalisation
  • State-of-the-art mathematical modelling techniques to gain insight into the processes that drive human learning and generalisation


  • Increased training efficiency—by developing programs that maximise generalisation without increasing length of training
  • Increased insights into trainees’ sensitivity to biased evidence and improved ability to adjust/correct for these biases

Successful applications

  • Generalisation training strategies successfully utilised to improve children’s learning of scientific concepts (Hayes et al., 2003)
  • Generalisation strategies incorporated into a program for improved understanding of climate science (Kary, Newell, & Hayes, 2018)
  • Recent work examined how people generalise from a sample of evidence when this evidence is biased.

Capabilities and facilities

  • Access to specialist software for mathematical modelling of human learning and generalisation performance