2335521
Project Grant
Overview
Grant Description
Sbir Phase I: Thinkquery: Empowering people to thrive in a complex world -this small business innovation research (SBIR) Phase I project empowers individuals with enhanced cognitive skills essential for success and innovation in the modern world. In today's global economy, the ability to think critically and creatively is crucial, but many people face developmental hurdles that hinder their economic competitiveness.
Unlike existing cognitive tools, this innovation offers a user-friendly, chat-based approach that leverages each individual's language skills to cultivate transferable thinking abilities. The solution guides users through a systematic problem-solving process, helping them map their mental models, fostering metacognition, and enabling them to challenge assumptions and biases.
Ultimately, the technology equips users to better comprehend and address a wide range of challenges. This project's primary aim is to support the diverse and underserved populations enrolled in community colleges. The technology enables students to learn at their own pace, break down developmental courses into shorter modules, and tailor content to align with their specific career aspirations.
This adaptability and accessibility have the potential to transform education, providing a flexible and effective learning tool for a wide audience. The team addresses a pressing societal need for improved cognitive skills, enhancing not only individual prospects but also contributing to the nation's economic vitality. This small business innovation research (SBIR) Phase I project focuses on enabling individuals to effectively navigate complex challenges in the 21st century by leveraging the Distinctions, Systems, Relationships, and Perspectives (DSRP) theory within a machine-interpretable data structure integrated into a visual-structural recommender system.
The technical objective is to empower users with a tool that facilitates in-depth exploration and understanding of various problems and topics. The project's key components develop algorithms that incorporate DSRP theory and artificial intelligence (AI)/machine learning (ML) techniques to create collaborative filtering and content-based filtering for generating user-specific questions. The solution creates a comprehensive reporting schema, coding, and statistical tools to validate empirical measures for different usage scenarios.
The team also defines use case conditions and user experience design parameters to enhance the effectiveness of the technology. Initially, this project targets diverse, underserved, and disadvantaged students in developmental education programs who often struggle with college-level coursework. The innovation's accessibility, driven by the use of everyday language as inputs, makes it a commercially viable cognitive skills training technology with reduced friction and greater user-friendliness compared to existing solutions.
The technology addresses both technical challenges and educational barriers associated with mind-mapping technologies, promising a significant impact on learning and problem-solving capabilities. 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. - Subawards are not planned for this award.
Unlike existing cognitive tools, this innovation offers a user-friendly, chat-based approach that leverages each individual's language skills to cultivate transferable thinking abilities. The solution guides users through a systematic problem-solving process, helping them map their mental models, fostering metacognition, and enabling them to challenge assumptions and biases.
Ultimately, the technology equips users to better comprehend and address a wide range of challenges. This project's primary aim is to support the diverse and underserved populations enrolled in community colleges. The technology enables students to learn at their own pace, break down developmental courses into shorter modules, and tailor content to align with their specific career aspirations.
This adaptability and accessibility have the potential to transform education, providing a flexible and effective learning tool for a wide audience. The team addresses a pressing societal need for improved cognitive skills, enhancing not only individual prospects but also contributing to the nation's economic vitality. This small business innovation research (SBIR) Phase I project focuses on enabling individuals to effectively navigate complex challenges in the 21st century by leveraging the Distinctions, Systems, Relationships, and Perspectives (DSRP) theory within a machine-interpretable data structure integrated into a visual-structural recommender system.
The technical objective is to empower users with a tool that facilitates in-depth exploration and understanding of various problems and topics. The project's key components develop algorithms that incorporate DSRP theory and artificial intelligence (AI)/machine learning (ML) techniques to create collaborative filtering and content-based filtering for generating user-specific questions. The solution creates a comprehensive reporting schema, coding, and statistical tools to validate empirical measures for different usage scenarios.
The team also defines use case conditions and user experience design parameters to enhance the effectiveness of the technology. Initially, this project targets diverse, underserved, and disadvantaged students in developmental education programs who often struggle with college-level coursework. The innovation's accessibility, driven by the use of everyday language as inputs, makes it a commercially viable cognitive skills training technology with reduced friction and greater user-friendliness compared to existing solutions.
The technology addresses both technical challenges and educational barriers associated with mind-mapping technologies, promising a significant impact on learning and problem-solving capabilities. 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. - Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Ithaca,
New York
14850-9435
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 7% from $275,000 to $295,000.
Cabrera Research Lab was awarded
Project Grant 2335521
worth $295,000
from National Science Foundation in January 2024 with work to be completed primarily in Ithaca New York United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I: Chat-Based Technology to Enhance Cognition and Complex Reasoning
Abstract
This Small Business Innovation Research (SBIR) Phase I project empowers individuals with enhanced cognitive skills essential for success and innovation in the modern world. In today's global economy, the ability to think critically and creatively is crucial, but many people face developmental hurdles that hinder their economic competitiveness. Unlike existing cognitive tools, this innovation offers a user-friendly, chat-based approach that leverages each individual's language skills to cultivate transferable thinking abilities. The solution guides users through a systematic problem-solving process, helping them map their mental models, fostering metacognition, and enabling them to challenge assumptions and biases. Ultimately, the technology equips users to better comprehend and address a wide range of challenges. This project's primary aim is to support the diverse and underserved populations enrolled in community colleges. The technology enables students to learn at their own pace, break down developmental courses into shorter modules, and tailor content to align with their specific career aspirations. This adaptability and accessibility have the potential to transform education, providing a flexible and effective learning tool for a wide audience. The team addresses a pressing societal need for improved cognitive skills, enhancing not only individual prospects but also contributing to the nation's economic vitality.
This Small Business Innovation Research (SBIR) Phase I project focuses on enabling individuals to effectively navigate complex challenges in the 21st century by leveraging the Distinctions, Systems, Relationships, and Perspectives (DSRP) Theory within a machine-interpretable data structure integrated into a visual-structural recommender system. The technical objective is to empower users with a tool that facilitates in-depth exploration and understanding of various problems and topics. The project's key components develop algorithms that incorporate DSRP theory and Artificial Intelligence (AI)/Machine Learning (ML) techniques to create collaborative filtering and content-based filtering for generating user-specific questions. The solution creates a comprehensive reporting schema, coding, and statistical tools to validate empirical measures for different usage scenarios. The team also defines use case conditions and user experience design parameters to enhance the effectiveness of the technology. Initially, this project targets diverse, underserved, and disadvantaged students in developmental education programs who often struggle with college-level coursework. The innovation's accessibility, driven by the use of everyday language as inputs, makes it a commercially viable cognitive skills training technology with reduced friction and greater user-friendliness compared to existing solutions. The technology addresses both technical challenges and educational barriers associated with mind-mapping technologies, promising a significant impact on learning and problem-solving capabilities.
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.
Topic Code
LC
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 11/20/24
Period of Performance
1/15/24
Start Date
12/31/24
End Date
Funding Split
$295.0K
Federal Obligation
$0.0
Non-Federal Obligation
$295.0K
Total Obligated
Activity Timeline
Transaction History
Modifications to 2335521
Additional Detail
Award ID FAIN
2335521
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
XWHNPJC17FY5
Awardee CAGE
None
Performance District
NY-19
Senators
Kirsten Gillibrand
Charles Schumer
Charles Schumer
Modified: 11/20/24