Research

Perceptual Learning: Basic Research and Modeling

This work focuses on high-level perceptual learning, especially research and modeling of human abilities to discover and encode abstract relations (as in perception of a shape, a melody, or in language).

We are also working to relate examples of so-called high-level and low-level perceptual learning – an effort that is tending to show that, following Eleanor Gibson's classic view, selection and discovery of invariance characterize perceptual learning across levels, and even improvements that appear "low-level" and sensory involve substantial contributions of perceptual organization.

Researchers

  • Philip J. Kellman Philip J. Kellman
  • Everett Mettler Everett Mettler
  • Carolyn Bufford Carolyn Bufford

Collaborators

  • Christine Massey Christine Massey (Penn)
  • face Hongjing Lu (UCLA)
  • face Patrick Garrigan (SJU)

Selected Publications

Bufford, C. A., Mettler, E., Geller, E. H., & Kellman, P. J. (2014). The psychophysics of algebra expertise: Mathematics perceptual learning interventions produce durable encoding changes. In P. Bellow, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 272-277). Austin, TX: Cognitive Science Society.
Mettler, E., & Kellman, P. J. (2014). Adaptive response-time-based category sequencing in perceptual learning. Vision Research, 99, 111-123.
Alibali, M., Kalish, C., Rogers, T. T., Massey, C., Kellman, P., Sloutsky, V., McClelland, J. L., & Mickey, K. W. (2015). Connecting learning, memory, and representation in math education. Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Thai, K. P., Krasne, S., & Kellman, P. J. (2015). Adaptive perceptual learning in electrocardiography: The synergy of passive and active classification. Proceedings of the 37th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Rimoin, L., Altieri, L., Craft, N., Krasne, S., & Kellman, P. J. (2015). Training pattern recognition of skin lesion morphology, configuration, and distribution. Journal of the American Academy of Dermatology, 72(3), 489-495.
Kellman, P.J., & Massey, C.M. (2013) Perceptual learning, cognition, and expertise. In B.H. Ross (Ed.), The Psychology of Learning and Motivation (Vol. 58, 117-165). Amsterdam: Elsevier Inc.
Mettler, E., Massey, C., & Kellman, P. J. (2011) Improving adaptive learning technology through the use of response times. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 2532-2537). Boston, MA: Cognitive Science Society.
Thai, K. P., Mettler, E., & Kellman, P. J. (2011). Basic information processing effects from perceptual learning in complex, real-world domains. In L. Carlson, C. Holscher, & T Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp. 555-560). Boston, MA: Cognitive Science Society.
Kellman, P. J. & Garrigan, P. B. (2009). Perceptual learning and human expertise. Physics of Life Reviews, 6(2), 53-84.
Garrigan, P.B. & Kellman, P.J. (2008). Perceptual learning depends on perceptual constancy. Proceedings of the National Academy of Sciences (USA), Vol. 105, No. 6, 2248-2253.
Kellman, P.J. (2002). Perceptual learning.In R. Gallistel (Ed.), Stevens' handbook of experimental psychology, Third edition, Vol. 3 (Learning, motivation and emotion), John Wiley & Sons, 259-299.