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Philip J. Kellman

  •  Home
  •  Publications
    16
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    11

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  • All publications (16)
  •  55
    For deep networks, the whole equals the sum of the parts
    with Nicholas Baker, Patrick Garrigan, Austin Phillips, and Hongjing Lu
    Behavioral and Brain Sciences 46. 2023.
    Deep convolutional networks exceed humans in sensitivity to local image properties, but unlike biological vision systems, do not discover and encode abstract relations that capture important properties of objects and events in the world. Coupling network architectures with additional machinery for encoding abstract relations will make deep networks better models of human abilities and more versatile and capable artificial devices.
    Cognitive Sciences
  •  230
    Perceptual learning and the technology of expertise
    with Christine Massey, Zipora Roth, Timothy Burke, Joel Zucker, Amanda Saw, Katherine E. Aguero, and Joseph A. Wise
    Pragmatics and Cognition 16 (2): 356-405. 2008.
    Learning in educational settings most often emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other, equally important components of learning, especially improvements produced by experience in the extraction of information: Perceptual learning. Here we describe research that combines principles of perceptual learning with computer technology to address persistent difficulties in mathematics learning. We report three experiments in which we developed and tes…Read more
    Learning in educational settings most often emphasizes declarative and procedural knowledge. Studies of expertise, however, point to other, equally important components of learning, especially improvements produced by experience in the extraction of information: Perceptual learning. Here we describe research that combines principles of perceptual learning with computer technology to address persistent difficulties in mathematics learning. We report three experiments in which we developed and tested perceptual learning modules to address issues of structure extraction and fluency in relation to algebra and fractions. PLMs focus students’ learning on recognizing and discriminating, or mapping key structures across different representations or transformations. Results showed significant and persisting learning gains for students using PLMs. PLM technology offers promise for addressing neglected components of learning: Pattern recognition, structural intuition, and fluency. Using PLMs as a complement to other modes of instruction may allow students to overcome chronic problems in learning.
    LearningContinental Philosophy
  •  3
    Improving Adaptive Learning Technology through the Use of Response Times
    with Everett Mettler and Christine Massey
  •  142
    Perception of partly occluded objects in infancy* 1
    with Elizabeth S. Spelke
    Cognitive Psychology 15 (4). 1983.
    Four-month-old infants sometimes can perceive the unity of a partly hidden object. In each of a series of experiments, infants were habituated to one object whose top and bottom were visible but whose center was occluded by a nearer object. They were then tested with a fully visible continuous object and with two fully visible object pieces with a gap where the occluder had been. Pattems of dishabituation suggested that infants perceive the boundaries of a partly hidden object by analyzing the m…Read more
    Four-month-old infants sometimes can perceive the unity of a partly hidden object. In each of a series of experiments, infants were habituated to one object whose top and bottom were visible but whose center was occluded by a nearer object. They were then tested with a fully visible continuous object and with two fully visible object pieces with a gap where the occluder had been. Pattems of dishabituation suggested that infants perceive the boundaries of a partly hidden object by analyzing the movements of its surfaces: infants perceived a connected object when its ends moved in a common translation behind the occluder. Infants do not appear to perceive a connected object by analyzing the colors and forms of surfaces: they did not perceive a connected object when its visible parts were stationary, its color was homogeneous, its edges were aligned, and its shape was simple and regular. These findings do not support the thesis, from gestalt psychology, that object perception first arises as a consequence of a tendency to perceive the simplest, most regular configuration, or the Piagetian thesis that object perception depends on the prior coordination of action. Perception of objects may depend on an inherent conception of what an object is.
    PerceptionCognitive Sciences
  •  84
    Interpolation processes in object perception: Reply to Anderson (2007)
    with Patrick Garrigan, Thomas F. Shipley, and Brian P. Keane
    Psychological Review 114 (2): 488-502. 2007.
    Aspects of Consciousness
  •  7
    Perceptual learning
    In J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology, Wiley. 2002.
    Aspects of Consciousness
  •  215
    Finding the Pope in the pizza: Abstract invariants and cognitive constraints on perceptual learning
    with John E. Hummel
    Behavioral and Brain Sciences 21 (1): 30-30. 1998.
    Schyns, Goldstone & Thibaut argue that categorization experience results in the learning of new perceptual features that are not derivable from the learner's existing feature set. We explore the meaning and implications of this “nonderivability” claim and relate it to the question of whether perceptual invariants are learnable, and if so, what might be entailed in learning them.
    Science of Perception, Misc
  • Learning, motivation, and emotion
    In J. Wixted & H. Pashler (eds.), Stevens' Handbook of Experimental Psychology, Wiley. pp. 267. 2002.
  •  269
    Perceptual Learning Modules in Mathematics: Enhancing Students' Pattern Recognition, Structure Extraction, and Fluency
    with Christine M. Massey and Ji Y. Son
    Topics in Cognitive Science 2 (2): 285-305. 2010.
    Philosophy of Cognitive Science
  •  97
    Is interpolation cognitively encapsulated? Measuring the effects of belief on Kanizsa shape discrimination and illusory contour formation
    with Brian P. Keane, Hongjing Lu, Thomas V. Papathomas, and Steven M. Silverstein
    Cognition 123 (3): 404-418. 2012.
    Modularity in Cognitive ScienceIllusion and HallucinationScience of ConsciousnessConscious and Uncon…Read more
    Modularity in Cognitive ScienceIllusion and HallucinationScience of ConsciousnessConscious and Unconscious Learning
  •  47
    Object Interpolation in Three Dimensions
    with Patrick Garrigan and Thomas F. Shipley
    Psychological Review 112 (3): 586-609. 2005.
    Areas of Mathematics
  •  101
    From Flashes to Edges to Objects: Recovery of Local Edge Fragments Initiates Spatiotemporal Boundary Formation
    with Gennady Erlikhman
    Frontiers in Psychology 7. 2016.
    Philosophy of Cognitive Science
  • Discontinuity theory and the perception of illusory figures
    with T. F. Shipley
    Bulletin of the Psychonomic Society 26 (6): 516-516. 1988.
  • Interpolation processes in visual object perception-evidence for a discontinuity theory
    with T. F. Shipley
    Bulletin of the Psychonomic Society 25 (5): 334-334. 1987.
    Philosophy of ConsciousnessAspects of Consciousness
  •  93
    Postscript: Identity and constraints in models of object formation
    with Patrick Garrigan, Thomas F. Shipley, and Brian P. Keane
    Psychological Review 114 (2): 502-508. 2007.
  •  120
    Non-rigid illusory contours and global shape transformations defined by spatiotemporal boundary formation
    with Gennady Erlikhman and Yang Z. Xing
    Frontiers in Human Neuroscience 8. 2014.
    Philosophy of Neuroscience
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