
NSF Org: |
IIS Division of Information & Intelligent Systems |
Recipient: |
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Initial Amendment Date: | January 17, 2018 |
Latest Amendment Date: | May 23, 2022 |
Award Number: | 1749917 |
Award Instrument: | Continuing Grant |
Program Manager: |
Andy Duan
yduan@nsf.gov (703)292-4286 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
Start Date: | June 1, 2018 |
End Date: | May 31, 2025 (Estimated) |
Total Intended Award Amount: | $550,000.00 |
Total Awarded Amount to Date: | $660,000.00 |
Funds Obligated to Date: |
FY 2019 = $111,655.00 FY 2020 = $221,494.00 FY 2021 = $100,819.00 FY 2022 = $103,533.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
11200 SW 8TH ST MIAMI FL US 33199-2516 (305)348-2494 |
Sponsor Congressional District: |
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Primary Place of Performance: |
FL US 33199-0001 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | Robust Intelligence |
Primary Program Source: |
01002021DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT 01002021DB NSF RESEARCH & RELATED ACTIVIT 01001920DB NSF RESEARCH & RELATED ACTIVIT 01001819DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.070 |
ABSTRACT
Why do certain stories, but not others, resonate so powerfully with certain populations? Stories (a.k.a. narratives) are powerful: where rational argument fails, a single story can drive home a point, change a mind, and even change a life. What specific structures underlie the power of narrative, and what new artificial intelligence (AI) techniques are needed to learn these structures automatically so we can leverage them in applications? This project seeks to develop these new AI techniques to automatically uncover and confirm the fundamental structures underlying narrative, developing and testing with data drawn from the domains of education and culture. This work will be of broad relevance to developing more intelligent machines, understanding the mind and brain, and improving education. It will produce fundamental insights into a universal form of communication (narrative), providing a potentially transformative new set of tools to researcher and educators.
The project will develop new machine learning and natural language processing approaches to learning key aspects of narrative structure. The basic structure of a narrative involves the plot, a time-ordered sequence of important events, and the plot can be divided into three levels of structure: (1) plot pieces, (2) archetypal characters, and (3) narrative arcs. The PI and his students will first learn to extract these three types of narrative structure, the third of which (narrative arcs) is as-yet untried, using novel combinations of existing grammar learning approaches and Bayesian approaches, specifically the PI's Analogical Story Merging (ASM) algorithm, the Infinite Relational Model (IRM), and iterative learning. Second, the researchers will test hypotheses that reflect why specific stories are persuasive to specific cultures, and apply these insights to improving minority engagement in STEM and computing in middle-school classrooms in Miami Dade County Public Schools. Third, the researchers will seek to uncover systematic regularities in professional education cases (such as business cases, or medical case reports) that will lead to the ability to make computational predictions as to which cases should be most effective in the classroom.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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