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High-probability grants
According to our matching algorithm, Bob Rehder is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 1996 |
Rehder, Bob |
F31Activity Code Description:
To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Nature of Coherent Categories @ University of Colorado At Boulder |
0.954 |
| 2006 — 2010 |
Rehder, Bob |
N/AActivity Code Description:
No activity code was retrieved: click on the grant title for more information |
An Eyetracking Category Learning Model
People perceive objects in the world not as completely novel entities, but rather, as examples of a type, kind, or category. An animal is recognized as a member of a particular species, a medical patient is treated as a case of a particular disease, and so on. The processes by which people categorize objects is a central question in the cognitive sciences, and current theories of categorization all agree that tracking a person's attention to features and characteristics of objects is key to understanding the underlying processes. But until recently, it was very difficult for researchers to measure attention as a source of evidence for theories of categorization.
With support of the National Science Foundation, Dr. Rehder aims to advance theories of categorization by tracking people's eye movements as they learn new visual categories. Eye movements have been shown to closely follow the focus of attention as it roams over a visual object or scene. Dr. Rehder will use eye movements to gauge the features and characteristics of objects that are used to learn new categories, and eventually used to categorize objects fluently in skilled performance. The knowledge to be gained by this research may provide a basis for better understanding the cognitive malfunctions that occur with attentional deficits. More generally, this research may inform educational practice in contexts where academic performance depends on how the student categorizes a given problem to be solved.
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