Sunday, August 23, 2015

Strengthening Human Adaptive Reasoning and Problem-Solving (SHARP)


iarpa.gov |  Adaptive reasoning and problem-solving are increasingly valuable for information-oriented workplaces, where inferences from sparse, voluminous, or conflicting data must be drawn, validated, and communicated—often under stressful, time-sensitive conditions. In such contexts, one’s ability to accurately update one’s mental models, make valid conclusions, and effectively deploy attention and other cognitive resources is critical. Accordingly, optimizing an analyst’s adaptive reasoning could pay large dividends in the quality of their analytic conclusions and information products. Given adaptive reasoning tests’ high predictive value for performance and productivity, proven methods for strengthening adaptive reasoning and problem-solving could have significant benefits for society in general, as well as for individuals whose work is both analytical and cognitively demanding. Intriguingly, some recent research suggests that these capabilities may be strengthened, even among high-performing adults. Despite some promising results, however, there are methodological and practical shortcomings that currently limit the direct applicability of this research for the Intelligence Community.

Therefore, the Strengthening Human Adaptive Reasoning and Problem-Solving (SHARP) Program is seeking to fund rigorous, high-quality research to address these limitations and advance the science on optimizing human adaptive reasoning and problem-solving. The goal of the program is to test and validate interventions that have the potential to significantly improve these capabilities, leading to improvements in performance for high-performing adults in information-rich environments.

The research funded in this program will use innovative and promising approaches from a variety of fields with an emphasis on collecting data from a set of cognitive, behavioral, and biological outcome measures in order to determine convergent validity of successful approaches. It is anticipated that successful teams will be multidisciplinary, and may include (but not be limited to) research expertise in cognitive and behavioral neuroscience; psychology and psychometrics; human physiology and neurophysiology; structural and functional imaging; molecular biology and genetics; human subjects research design, methodology, and regulations; mathematical statistics and modeling; data visualization and analytics

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