2451139
Project Grant
Overview
Grant Description
SBIR Phase I: Education and training for an AI integrated future: Mixed-reality, competency based learning.
The broader/commercial impact of this SBIR Phase I project leverages adaptive and personalized mixed-reality training solutions to address the critical challenge of workforce displacement due to artificial intelligence (AI).
AI and automation technologies will displace between 400 million and 800 million individuals globally by 2030, requiring up to 375 million workers to switch occupational categories and learn new skills.
An adaptive learning platform will democratize access to high-quality, personalized training experiences, serving displaced workers, older persons, economically disadvantaged youth, and vocational learners.
The platform accelerates the acquisition of essential competencies in AI literacy, data science, healthcare technical roles, and vocational skills through immersive, evidence-based learning experiences.
This technology bridges the growing skills gap by validating existing competencies while developing new ones, enabling faster workforce transitions and creating new pathways to employment in an AI-integrated economy.
This Small Business Innovation Research (SBIR) Phase I project develops a novel adaptive learning platform through three core technological innovations: a skills engine, an authoring tool, and an extended reality (XR) player.
The skills engine uses generative AI and RAG to identify and map key competencies, creating personalized learning pathways based on individual skill profiles.
The authoring tool transforms the creation of adaptive learning content through AI-assisted scenario generation, automated asset creation, and integrated assessment tools, reducing development time and costs while maintaining high educational standards.
The XR player delivers these experiences through augmented and virtual reality, adapting in real-time to learner performance and capturing analytics for competency validation.
The platform architecture integrates these components seamlessly while maintaining compliance with IEEE standards and RAMP certification requirements, establishing a new benchmark for evidence-based, adaptive learning in mixed reality 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 leverages adaptive and personalized mixed-reality training solutions to address the critical challenge of workforce displacement due to artificial intelligence (AI).
AI and automation technologies will displace between 400 million and 800 million individuals globally by 2030, requiring up to 375 million workers to switch occupational categories and learn new skills.
An adaptive learning platform will democratize access to high-quality, personalized training experiences, serving displaced workers, older persons, economically disadvantaged youth, and vocational learners.
The platform accelerates the acquisition of essential competencies in AI literacy, data science, healthcare technical roles, and vocational skills through immersive, evidence-based learning experiences.
This technology bridges the growing skills gap by validating existing competencies while developing new ones, enabling faster workforce transitions and creating new pathways to employment in an AI-integrated economy.
This Small Business Innovation Research (SBIR) Phase I project develops a novel adaptive learning platform through three core technological innovations: a skills engine, an authoring tool, and an extended reality (XR) player.
The skills engine uses generative AI and RAG to identify and map key competencies, creating personalized learning pathways based on individual skill profiles.
The authoring tool transforms the creation of adaptive learning content through AI-assisted scenario generation, automated asset creation, and integrated assessment tools, reducing development time and costs while maintaining high educational standards.
The XR player delivers these experiences through augmented and virtual reality, adapting in real-time to learner performance and capturing analytics for competency validation.
The platform architecture integrates these components seamlessly while maintaining compliance with IEEE standards and RAMP certification requirements, establishing a new benchmark for evidence-based, adaptive learning in mixed reality 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 / SMALL BUSINESS TECHNOLOGY TRANSFER PHASE I PROGRAMS", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF24579
Grant Program (CFDA)
Awarding Agency
Place of Performance
West Haven,
Connecticut
06516-7932
United States
Geographic Scope
Single Zip Code
Mixta Re was awarded
Project Grant 2451139
worth $304,200
from in January 2025 with work to be completed primarily in West Haven Connecticut 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: Education and Training for an AI Integrated Future: Mixed-Reality, Competency Based Learning
Abstract
The broader/commercial impact of this SBIR Phase I project leverages adaptive and personalized mixed-reality training solutions to address the critical challenge of workforce displacement due to artificial intelligence (AI). AI and automation technologies will displace between 400 million and 800 million individuals globally by 2030, requiring up to 375 million workers to switch occupational categories and learn new skills. An adaptive learning platform will democratize access to high-quality, personalized training experiences, serving displaced workers, older persons, economically disadvantaged youth, and vocational learners. The platform accelerates the acquisition of essential competencies in AI literacy, data science, healthcare technical roles, and vocational skills through immersive, evidence-based learning experiences. This technology bridges the growing skills gap by validating existing competencies while developing new ones, enabling faster workforce transitions and creating new pathways to employment in an AI-integrated economy.
This Small Business Innovation Research (SBIR) Phase I project develops a novel adaptive learning platform through three core technological innovations: a skills engine, an authoring tool, and an extended reality (XR) player. The skills engine uses Generative AI and RAG to identify and map key competencies, creating personalized learning pathways based on individual skill profiles. The authoring tool transforms the creation of adaptive learning content through AI-assisted scenario generation, automated asset creation, and integrated assessment tools, reducing development time and costs while maintaining high educational standards. The XR player delivers these experiences through augmented and virtual reality, adapting in real-time to learner performance and capturing analytics for competency validation. The platform architecture integrates these components seamlessly while maintaining compliance with IEEE standards and RAMP cer
Topic Code
LC
Solicitation Number
NSF 24-579
Status
(Ongoing)
Last Modified 1/22/25
Period of Performance
1/1/25
Start Date
12/31/25
End Date
Funding Split
$304.2K
Federal Obligation
$0.0
Non-Federal Obligation
$304.2K
Total Obligated
Activity Timeline
Transaction History
Modifications to 2451139
Additional Detail
Award ID FAIN
2451139
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
PPP3BMM2CQT6
Awardee CAGE
9WU66
Performance District
CT-03
Senators
Richard Blumenthal
Christopher Murphy
Christopher Murphy
Modified: 1/22/25