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Dr Dario Krpan

Dr Stuart Mills

This course is available on the MSc in Behavioural Science. This course is not available as an outside option.

When Psychology and Economics got "married", the product was Behavioural Science. Although this discipline has elevated theoretical and practical understanding of human behaviour to previously unseen heights, recent technological developments have produced new insights in understanding and predicting people's actions that not only supplement traditional tools of behavioural science but also go beyond them. The future of the discipline will therefore likely depend on how effectively behavioural scientists can harness new developments in technology to understand and change the way people act.

The aim of this course is to a) Introduce major technological advancements that are relevant for predicting, influencing, and understanding human behaviour; b) Outline how they supplement and extend commonly used tools of behavioural change; and c) Examine how they can be used to propel behavioural science into the future. The course will tackle behavioural science in relation to motion tracking, virtual environments, social robotics, social networks, and other relevant developments in information technology.

Example topics explored on the course: Understanding minds by reading bodies; Implications of motion tracking for behavioural science; Changing behaviour through gamification; Social robots: Our new friends?; Behavioural science in virtual worlds; Behavioural informatics; Change thyself: Using technology to influence our own behaviour; Digital footprints and human behaviour; Psychological targeting in digital age; The ethics of emerging technologies in the context of behavioural science.

10 hours of lectures and 10 hours of seminars in the LT.

Krpan, D., & Urbanik, M. (2020). From Libertarian Paternalism to Liberalism: Behavioural Science and Policy in an Age of New Technology.

Kersten-van Dijk, E. T., Westerink, J. H., Beute, F., & IJsselsteijn, W. A. (2017). Personal informatics, self-insight, and behavior change: A critical review of current literature. Human–Computer Interaction, 32(5-6), 268-296.

Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802-5805.

Sailer, M., Hense, J. U., Mayr, S. K., & Mandl, H. (2017). How gamification motivates: An experimental study of the effects of specific game design elements on psychological need satisfaction. Computers in Human Behavior, 69, 371-380.

Broadbent, E. (2017). Interactions with robots: The truths we reveal about ourselves. Annual Review of Psychology, 68, 627-652.

Dissertation (100%, 10000 words) post-summer term.

You are required to write a 10,000 word dissertation (replacing the video presentation). You are expected to attend the course teaching on the half-unit that you chose to write your dissertation on.

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.