Behavioural Science in an Age of New Technology - Dissertation
This information is for the 2020/21 session.
Dr Dario Krpan
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.
Stephen, D. G., Dixon, J. A., & Isenhower, R. W. (2009). Dynamics of representational change: Entropy, action, and cognition. Journal of Experimental Psychology: Human Perception and Performance, 35(6), 1811-1832.
Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D., Marlow, C., Settle, J. E., & Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489(7415), 295-298.
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.
Bailey, J. O., Bailenson, J. N., Flora, J., Armel, K. C., Voelker, D., & Reeves, B. (2015). The impact of vivid messages on reducing energy consumption related to hot water use. Environment and Behavior, 47(5), 570-592.
Pärnamets, P., Johansson, P., Hall, L., Balkenius, C., Spivey, M. J., & Richardson, D. C. (2015). Biasing moral decisions by exploiting the dynamics of eye gaze. Proceedings of the National Academy of Sciences, 112(13), 4170-4175.
Doherty, A. R., Caprani, N., Conaire, C. O., Kalnikaite, V., Gurrin, C., Smeaton, A. F., & O’Connor, N. E. (2011). Passively recognising human activities through lifelogging. Computers in Human Behavior, 27(5), 1948-1958.
Pavel, M., Jimison, H. B., Korhonen, I., Gordon, C. M., & Saranummi, N. (2015). Behavioral informatics and computational modeling in support of proactive health management and care. IEEE Transactions on Biomedical Engineering, 62(12), 2763-2775.
Matz, S. C., Kosinski, M., Nave, G., & Stillwell, D. J. (2017). Psychological targeting as an effective approach to digital mass persuasion. Proceedings of the National Academy of Sciences of the United States of America, 114 (48), 12714–12719.
Ward, A. F., Duke, K., Gneezy, A., & Bos, M. W. (2017). Brain drain: the mere presence of one’s own smartphone reduces available cognitive capacity. Journal of the Association for Consumer Research, 2(2), 140-154.
Twenge, J. M., Joiner, T. E., Rogers, M. L., & Martin, G. N. (2018). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among US adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3-17.
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.
Hutchesson, M. J., Rollo, M. E., Krukowski, R., Ells, L., Harvey, J., Morgan, P. J., ... & Collins, C. E. (2015). eHealth interventions for the prevention and treatment of overweight and obesity in adults: a systematic review with meta-analysis. Obesity Reviews, 16(5), 376-392.
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.
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Department: Psychological and Behavioural Science
Total students 2019/20: 17
Average class size 2019/20: 8
Controlled access 2019/20: Yes
Value: One Unit
Personal development skills
- Team working
- Problem solving
- Application of information skills
- Application of numeracy skills
- Specialist skills