11,609 research outputs found
A review of research into the development of radiologic expertise: Implications for computer-based training
Rationale and Objectives. Studies of radiologic error reveal high levels of variation between radiologists. Although it is known that experts outperform novices, we have only limited knowledge about radiologic expertise and how it is acquired.Materials and Methods. This review identifies three areas of research: studies of the impact of experience and related factors on the accuracy of decision-making; studies of the organization of expert knowledge; and studies of radiologists' perceptual processes.Results and Conclusion. Interpreting evidence from these three paradigms in the light of recent research into perceptual learning and studies of the visual pathway has a number of conclusions for the training of radiologists, particularly for the design of computer-based learning programs that are able to illustrate the similarities and differences between diagnoses, to give access to large numbers of cases and to help identify weaknesses in the way trainees build up a global representation from fixated regions
Spatial Aggregation: Theory and Applications
Visual thinking plays an important role in scientific reasoning. Based on the
research in automating diverse reasoning tasks about dynamical systems,
nonlinear controllers, kinematic mechanisms, and fluid motion, we have
identified a style of visual thinking, imagistic reasoning. Imagistic reasoning
organizes computations around image-like, analogue representations so that
perceptual and symbolic operations can be brought to bear to infer structure
and behavior. Programs incorporating imagistic reasoning have been shown to
perform at an expert level in domains that defy current analytic or numerical
methods. We have developed a computational paradigm, spatial aggregation, to
unify the description of a class of imagistic problem solvers. A program
written in this paradigm has the following properties. It takes a continuous
field and optional objective functions as input, and produces high-level
descriptions of structure, behavior, or control actions. It computes a
multi-layer of intermediate representations, called spatial aggregates, by
forming equivalence classes and adjacency relations. It employs a small set of
generic operators such as aggregation, classification, and localization to
perform bidirectional mapping between the information-rich field and
successively more abstract spatial aggregates. It uses a data structure, the
neighborhood graph, as a common interface to modularize computations. To
illustrate our theory, we describe the computational structure of three
implemented problem solvers -- KAM, MAPS, and HIPAIR --- in terms of the
spatial aggregation generic operators by mixing and matching a library of
commonly used routines.Comment: See http://www.jair.org/ for any accompanying file
Understanding and Affecting Student Reasoning About Sound Waves
Student learning of sound waves can be helped through the creation of
group-learning classroom materials whose development and design rely on
explicit investigations into student understanding. We describe reasoning in
terms of sets of resources, i.e. grouped building blocks of thinking that are
commonly used in many different settings. Students in our university physics
classes often used sets of resources that were different from the ones we wish
them to use. By designing curriculum materials that ask students to think about
the physics from a different view, we bring about improvement in student
understanding of sound waves. Our curriculum modifications are specific to our
own classes, but our description of student learning is more generally useful
for teachers. We describe how students can use multiple sets of resources in
their thinking, and raise questions that should be considered by both
instructors and researchers.Comment: 23 pages, 4 figures, 3 tables, 28 references, 7 notes. Accepted for
publication in the International Journal of Science Educatio
Literal Perceptual Inference
In this paper, I argue that theories of perception that appeal to Helmholtz’s idea of unconscious inference (“Helmholtzian” theories) should be taken literally, i.e. that the inferences appealed to in such theories are inferences in the full sense of the term, as employed elsewhere in philosophy and in ordinary discourse.
In the course of the argument, I consider constraints on inference based on the idea that inference is a deliberate acton, and on the idea that inferences depend on the syntactic structure of representations. I argue that inference is a personal-level but sometimes unconscious process that cannot in general be distinguished from association on the basis of the structures of the representations over which it’s defined. I also critique arguments against representationalist interpretations of Helmholtzian theories, and argue against the view that perceptual inference is encapsulated in a module
Perceptual Context in Cognitive Hierarchies
Cognition does not only depend on bottom-up sensor feature abstraction, but
also relies on contextual information being passed top-down. Context is higher
level information that helps to predict belief states at lower levels. The main
contribution of this paper is to provide a formalisation of perceptual context
and its integration into a new process model for cognitive hierarchies. Several
simple instantiations of a cognitive hierarchy are used to illustrate the role
of context. Notably, we demonstrate the use context in a novel approach to
visually track the pose of rigid objects with just a 2D camera
- …