2431521
Project Grant
Overview
Grant Description
SBIR Phase I: Revolutionizing learning through AI augmented debate centered instruction.
The broader/commercial impact of this SBIR Phase I project is to transform education by developing an artificial intelligence (AI) enhanced debate-centered learning platform.
This innovative technology addresses the crucial need for cultivating 21st-century skills in students, with a focus on critical thinking, communication, collaboration, and self-regulation.
The platform provides personalized and engaging debate experiences, aiming to democratize access to high-quality enrichment education, especially for underserved communities.
The innovation applies cutting-edge AI techniques to educational contexts, including multi-agent language systems, graph neural networks, and mixture of expert models, thereby enhancing scientific understanding.
The target market includes K-12 schools, universities, and workplace learning programs seeking cost-effective solutions to improve student outcomes and career readiness.
The technology offers a unique competitive advantage through its innovative integration of AI and debate pedagogy, providing a scalable solution for enhancing student outcomes and career readiness across diverse educational settings.
The business model focuses on scalable, subscription-based software distribution, with the potential for rapid adoption across educational institutions which aims to transform how students learn to think critically, debate with evidence and reasoning, and engage with complex ideas.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel artificial intelligence (AI) powered platform for debate-centered instruction, addressing the complex challenge of enhancing student learning outcomes through advanced technology integration in education.
The research objectives include developing an AI-powered learning management system for debate education, creating advanced natural language processing algorithms for argument analysis and feedback, and designing a scalable infrastructure for personalized learning experiences.
The proposed research will employ a multi-faceted approach, combining techniques from machine learning, educational data mining, and cognitive science.
Methods include developing and training specialized language models for debate contexts, implementing knowledge graph technologies for efficient information retrieval, and creating adaptive learning algorithms that respond to individual student growth over time.
The research will investigate innovative approaches for ethical AI implementation in educational contexts, focusing on transparent oversight, bias mitigation, and privacy protection while maximizing educational benefits.
Anticipated technical results include a functional prototype of the augmented debate-centered instruction platform, demonstrating improved learning outcomes in critical thinking and debate skills.
The research aims to advance the field of AI in education by tackling unique challenges in debate instruction, such as real-time argument evaluation and personalized feedback generation while providing insights into optimizing human-AI collaboration in complex learning environments.
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.
The broader/commercial impact of this SBIR Phase I project is to transform education by developing an artificial intelligence (AI) enhanced debate-centered learning platform.
This innovative technology addresses the crucial need for cultivating 21st-century skills in students, with a focus on critical thinking, communication, collaboration, and self-regulation.
The platform provides personalized and engaging debate experiences, aiming to democratize access to high-quality enrichment education, especially for underserved communities.
The innovation applies cutting-edge AI techniques to educational contexts, including multi-agent language systems, graph neural networks, and mixture of expert models, thereby enhancing scientific understanding.
The target market includes K-12 schools, universities, and workplace learning programs seeking cost-effective solutions to improve student outcomes and career readiness.
The technology offers a unique competitive advantage through its innovative integration of AI and debate pedagogy, providing a scalable solution for enhancing student outcomes and career readiness across diverse educational settings.
The business model focuses on scalable, subscription-based software distribution, with the potential for rapid adoption across educational institutions which aims to transform how students learn to think critically, debate with evidence and reasoning, and engage with complex ideas.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel artificial intelligence (AI) powered platform for debate-centered instruction, addressing the complex challenge of enhancing student learning outcomes through advanced technology integration in education.
The research objectives include developing an AI-powered learning management system for debate education, creating advanced natural language processing algorithms for argument analysis and feedback, and designing a scalable infrastructure for personalized learning experiences.
The proposed research will employ a multi-faceted approach, combining techniques from machine learning, educational data mining, and cognitive science.
Methods include developing and training specialized language models for debate contexts, implementing knowledge graph technologies for efficient information retrieval, and creating adaptive learning algorithms that respond to individual student growth over time.
The research will investigate innovative approaches for ethical AI implementation in educational contexts, focusing on transparent oversight, bias mitigation, and privacy protection while maximizing educational benefits.
Anticipated technical results include a functional prototype of the augmented debate-centered instruction platform, demonstrating improved learning outcomes in critical thinking and debate skills.
The research aims to advance the field of AI in education by tackling unique challenges in debate instruction, such as real-time argument evaluation and personalized feedback generation while providing insights into optimizing human-AI collaboration in complex learning environments.
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
Castro Valley,
California
94546-3306
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.
Debater Hub was awarded
Project Grant 2431521
worth $295,000
from National Science Foundation in September 2024 with work to be completed primarily in Castro Valley California 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: Revolutionizing Learning Through AI Augmented Debate Centered Instruction
Abstract
The broader/commercial impact of this SBIR Phase I project is to transform education by developing an Artificial Intelligence (AI) enhanced debate-centered learning platform. This innovative technology addresses the crucial need for cultivating 21st-century skills in students, with a focus on critical thinking, communication, collaboration, and self-regulation. The platform provides personalized and engaging debate experiences, aiming to democratize access to high-quality enrichment education, especially for underserved communities. The innovation applies cutting-edge AI techniques to educational contexts, including multi-agent language systems, graph neural networks, and mixture of expert models, thereby enhancing scientific understanding. The target market includes K-12 schools, universities, and workplace learning programs seeking cost-effective solutions to improve student outcomes and career readiness. The technology offers a unique competitive advantage through its innovative integration of AI and debate pedagogy, providing a scalable solution for enhancing student outcomes and career readiness across diverse educational settings. The business model focuses on scalable, subscription-based software distribution, with the potential for rapid adoption across educational institutions which aims to transform how students learn to think critically, debate with evidence and reasoning, and engage with complex ideas.
This Small Business Innovation Research (SBIR) Phase I project aims to develop a novel Artificial Intelligence (AI) powered platform for debate-centered instruction, addressing the complex challenge of enhancing student learning outcomes through advanced technology integration in education. The research objectives include developing an AI-powered Learning Management System for debate education, creating advanced natural language processing algorithms for argument analysis and feedback, and designing a scalable infrastructure for personalized learning experiences. The proposed research will employ a multi-faceted approach, combining techniques from machine learning, educational data mining, and cognitive science. Methods include developing and training specialized language models for debate contexts, implementing knowledge graph technologies for efficient information retrieval, and creating adaptive learning algorithms that respond to individual student growth over time. The research will investigate innovative approaches for ethical AI implementation in educational contexts, focusing on transparent oversight, bias mitigation, and privacy protection while maximizing educational benefits. Anticipated technical results include a functional prototype of the Augmented Debate-Centered Instruction platform, demonstrating improved learning outcomes in critical thinking and debate skills. The research aims to advance the field of AI in education by tackling unique challenges in debate instruction, such as real-time argument evaluation and personalized feedback generation while providing insights into optimizing human-AI collaboration in complex learning environments.
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
(Ongoing)
Last Modified 4/4/25
Period of Performance
9/15/24
Start Date
8/31/25
End Date
Funding Split
$295.0K
Federal Obligation
$0.0
Non-Federal Obligation
$295.0K
Total Obligated
Activity Timeline
Transaction History
Modifications to 2431521
Additional Detail
Award ID FAIN
2431521
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
JH1JD7M2EGN3
Awardee CAGE
11RZ3
Performance District
CA-14
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
Modified: 4/4/25