Teaching Resources


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Cognitive Science

This lecture series is part of the Cognitive Science third year subject (PSYC3211) and provides an introduction to topics in computational modelling

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Minds & Machines

This honours elective (PSYC4103) provides a gentle introduction to computational modelling of human cognition. It is structured around a series of case studies covering, inductive reasoning, concept learning, decision making and language acquisition. As such, discussions focus on whether - and how - the comparison between human and the machine learning tells us something useful about the mind.

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R for Psychological Science

Research methods in psychology have traditionally focused on study design and statistical analysis. The R statistical programming language is well-suited to these problems, but it's also very handy for solving many other problems facing behavioural scientists. This resource provides an introduction to R programming, with applications in psychological science. (Linked with the PSYC3361 internship program)

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Perception & Cognition

This lecture series is part of PSYC2071, and provides an introduction to cognitive psychology. The lecture materials present a brief history to the field, and then discuss key ideas in human attention, categorisation and reasoning. The content varies a little from year to year, but the slides below are representative:

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Learning Statistics with R

From 2011 to 2015 I used to teach introductory statistics, using the R statistical computing language, and wrote my own lecture notes, pitched at undergraduate psychology students. The notes became quite extensive, and are now effectively a book.

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Computational Cognitive Science

From 2010 to 2014, I used to run an introduction to computational cognitive science for undergraduate computer science students, in collaboration with Amy Perfors. The class hasn't been run in a few years, but we've archived most of the content.

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