Rachel Stephens

Room 226, Hughes Building Phone +61 (08) 8313 7402 Fax +61 (08) 8303 3770 rachel.stephens@adelaide.edu.au

Area of Research

Cognitive Psychology: Categorisation and feature inference

 Memberships

Australasian Society for Experimental Psychology
Computational Cognitive Science Lab
Brain and Cognition Unit
Golden Key International Honour Society

Awards

School of Psychology’s Excellence in Teaching Award (2009)
Brenda Nettle Bursary, AFUW-SA Trust Fund (June 2008)
Australian Postgraduate Award (commenced Feb 2007)
Defence Science and Technology Organisation Vacation Scholarship (Dec 2006 – Feb 2007)
University of Adelaide Undergraduate Research Scholarship (Nov 2005 – Feb 2006)
Norman Munn Prize for Psychology II, for achieving the highest Psychology II grade (2004)

Psychology Research Interests

My PhD research investigates several factors that influence the use of different knowledge to guide category-based feature induction. For example, one study addresses the impact of causal strength on the use and integration of causal feature relations and object similarities.

Other research with Prof. John Dunn has involved applying the iterated learning technique to examine people’s knowledge and reasoning when making predictions about both everyday and unfamiliar events. We are also extending this approach to investigate the basis of framing effects within legal decision making.

I have also been working with Dr. Carolyn Semmler on applied recognition and decision making research, such as investigating the effect of post-decision feedback on the relationship between confidence and accuracy.

Academic Papers

Stephens, R. G., Perfors, A. F. & Navarro, D. J. (2010). Social context effects on the impact of category labels. In S. Ohlsson & R. Catrambone (Eds). Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 1834-1849). Austin, TX: Cognitive Science Society

Stephens, R. G., Navarro, D. J., Dunn, J. C. & Lee, M. D. (2010). The effect of causal strength on the use of causal and similarity-based information in feature inference. In W. Christensen, E. Schier & J. Sutton (Eds.), ASCS09: Proceedings of the 9th Conference of the Australasian Society for Cognitive Science. Sydney: Macquarie Centre for Cognitive Science.

Stephens, R. G. & Navarro, D. J. (2008). One of these greebles is not like the others: Semi-supervised models for similarity structures. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 1996-2001). Austin, TX: Cognitive Science Society.