2232689
Project Grant
Overview
Grant Description
Sbir Phase I: A Platform to Connect Underserved and Underrepresented Communities to Science, Technology, Engineering and Mathematics (STEM) Careers - The Broader/Commercial Impact of This Small Business Innovation Research (SBIR) Phase I Project Is in Providing More Access to Educational Pathways, and Equitable Opportunities for Learning, Professional Development, and Career Growth to Marginalized Student Communities.
The Project Proposes the Development and Implementation of a Digital Human Element to Meet the Needs of These Impacted Individuals. The Project Is Not Such Organizations, but Also to Create Pathways to Equitable Opportunities for Those Coming from Marginalized Communities to Participate in Some of the Most Innovative Learning Modalities, While Studying for Some of the Most Promising STEM Careers.
The Intellectual Merit of This Project Lies in the Use of Big Data and Machine Learning in Personality and Skills Measurement. The Artificial Intelligence Algorithms Will Be Juxtaposed Onto Game Mechanics to Facilitate Ease of Use Due to the Familiarity with Other Existing User Interfaces. The Interface Has a Complex and Dynamic Personality Profiling Engine.
The Research Will Deliver Standards and Methodologies, Evaluate Existing Exchange Formats, Improve Accuracy Metrics for Neural Networks, and Deliver an Initial Digital Human Prototype. The Technology Will Create a Data Lake Containing Professions, Skills, Certificate Requirements, Social Media Profiles, Resumes, Recorded Interviews, and Other Online Activities That Are Shared by the Users for Establishing Personalized, Artificial Intelligence (AI)-Supported Career Growth Profiles.
Information in the Data Lake Will Be Curated to Facilitate the Development of Personalized Career Development Strategies. A Delta Lake Model Will Be Used to Continuously Stream Data with Improved Data Quality to Drive the Personalization Requirements of Both the Digital Human and the User.
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.
The Project Proposes the Development and Implementation of a Digital Human Element to Meet the Needs of These Impacted Individuals. The Project Is Not Such Organizations, but Also to Create Pathways to Equitable Opportunities for Those Coming from Marginalized Communities to Participate in Some of the Most Innovative Learning Modalities, While Studying for Some of the Most Promising STEM Careers.
The Intellectual Merit of This Project Lies in the Use of Big Data and Machine Learning in Personality and Skills Measurement. The Artificial Intelligence Algorithms Will Be Juxtaposed Onto Game Mechanics to Facilitate Ease of Use Due to the Familiarity with Other Existing User Interfaces. The Interface Has a Complex and Dynamic Personality Profiling Engine.
The Research Will Deliver Standards and Methodologies, Evaluate Existing Exchange Formats, Improve Accuracy Metrics for Neural Networks, and Deliver an Initial Digital Human Prototype. The Technology Will Create a Data Lake Containing Professions, Skills, Certificate Requirements, Social Media Profiles, Resumes, Recorded Interviews, and Other Online Activities That Are Shared by the Users for Establishing Personalized, Artificial Intelligence (AI)-Supported Career Growth Profiles.
Information in the Data Lake Will Be Curated to Facilitate the Development of Personalized Career Development Strategies. A Delta Lake Model Will Be Used to Continuously Stream Data with Improved Data Quality to Drive the Personalization Requirements of Both the Digital Human and the User.
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.
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=NSF22551
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Camarillo,
California
93010-7529
United States
Geographic Scope
Single Zip Code
Related Opportunity
22-551
Analysis Notes
Amendment Since initial award the total obligations have increased 7% from $275,000 to $295,000.
Nerrative Technology was awarded
Project Grant 2232689
worth $295,000
from National Science Foundation in April 2023 with work to be completed primarily in Camarillo California United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I:A platform to connect underserved and underrepresented communities to science, technology, engineering and mathemetics (STEM) careers
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is in providing more access to educational pathways, and equitable opportunities for learning, professional development, and career growth to marginalized student communities. The project proposes the development and implementation of a digital human element to meet the needs of these impacted individuals. The project is not such organizations, but also to create pathways to equitable opportunities for those coming from marginalized communities to participate in some of the most innovative learning modalities, while studying for some of the most promising STEM careers. _x000D_ _x000D_ The intellectual merit of this project lies in the use of big data and machine learning in personality and skills measurement. The artificial intelligence algorithms will be juxtaposed onto game mechanics to facilitate ease of use due to the familiarity with other existing user interfaces.The interface has a complex and dynamic personality profiling engine. The research will deliver standards and methodologies, evaluate existing exchange formats, improve accuracy metrics for neural networks, and deliver an initial digital human prototype. The technology will create a Data Lake containing professions, skills, certificate requirements, social media profiles, resumes, recorded interviews, and other online activities that are shared by the users for establishing personalized, artificial intelligence (AI)-supported career growth profiles. Information in the Data Lake will be curated to facilitate the development of personalized career development strategies. A Delta Lake model will be used to continuously stream data with improved data quality to drive the personalization requirements of both the digital human and the user._x000D_ _x000D_ 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 22-551
Status
(Complete)
Last Modified 12/5/23
Period of Performance
4/15/23
Start Date
3/31/24
End Date
Funding Split
$295.0K
Federal Obligation
$0.0
Non-Federal Obligation
$295.0K
Total Obligated
Activity Timeline
Transaction History
Modifications to 2232689
Additional Detail
Award ID FAIN
2232689
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
RF9XKJJ1CMQ8
Awardee CAGE
8WFT0
Performance District
CA-26
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $275,000 | 100% |
Modified: 12/5/23