Lecture: Remembering Spatial Location: Adaptive Combination Models
How do people remember spatial location?
to this question have varied from a cognitive map theory that
emphasizes veridicality to theories that emphasize errors and
distortions (and, in the extreme, deny that there are any metric
spatial representations at all). This talk will present an approach
that encompasses both accuracy and distortion, proposed originally
by Huttenlocher, Hedges, and Duncan (1991). In this category
adjustment model, people remember location both metrically and
categorically, and combine the two kinds of information in a
Bayesian way. The talk will review recent extensions and
explorations, and also examine applications to thinking about
Nora S. Newcombe is Professor of Psychology and James H. Glackin Distinguished Faculty Fellow at Temple University. Her Ph.D. is from Harvard University. Her research focuses on spatial cognition and development, including the nature of gender differences in spatial ability. She is also interested in the development of autobiographical and episodic memory. Dr. Newcombe is the author of numerous chapters, articles, and books, including Making Space with Janellen Huttenlocher (published by the MIT Press, 2000). Her work has been recognized by several awards, including the George A. Miller Award and the G. Stanley Hall Award. She is a member of the American Academy of Arts and Sciences and of the Society of Experimental Psychologists. She has served as Editor of the Journal of Experimental Psychology: General and Associate Editor of Psychological Bulletin, as well as on many grant panels and advisory boards. She is currently Principal Investigator of the NSF-funded Spatial Intelligence and Learning Center, whose mission is to understand human spatial cognition, with an emphasis on the idea that spatial knowledge and skills can be improved, and to apply the resulting knowledge to foster spatial learning, especially in STEM disciplines.
This lecture is presented by the Human Factors in GISciences Lab