Abstract & Details
Description
Award ID: 2151654
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project seeks to increase the competitive employability of individuals with developmental disabilities. For individuals with developmental disabilities (autism spectrum disorder and other intellectual disabilities) employment disparities are far greater than their non-disabled peers; Approximately 20% of working-age adults supported by state developmental disability agencies are employed in a paid job and only 15% were employed competitively. The proposed project will develop a product for school districts and higher education establishments to address the needs of approximately 8 million intellectually disadvantaged individuals in the United States education system. The implementation of this innovation seeks to impact the rates of employment in this population, resulting in increases in personal income, reduction of poverty levels, and better health outcomes for individuals. This Small Business Technology Transfer (STTR) Phase I project plans to create a scalable software framework which integrates, evaluates, and analyzes data from school districts and higher education programs in order to enable the use of machine learning to improve the relationship between transition intervention methods and employment outcomes. Using this innovation, school districts would be able accurately predetermine an individuals ability to successfully perform tasks associated with employment. Higher education programs which enroll adults with developmental disabilities may then effectively scale and develop an individuals employability skills. The framework will provide structured data collection, data alignment, and data interlinking for roadmaps which will be implemented into the product, enabling educators and individuals to interact, learning how employability programmatic factors and educator corrective actions contribute to employability skills development. 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.
NSF Program Director: Rajesh Mehta
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project seeks to increase the competitive employability of individuals with developmental disabilities. For individuals with developmental disabilities (autism spectrum disorder and other intellectual disabilities) employment disparities are far greater than their non-disabled peers; Approximately 20% of working-age adults supported by state developmental disability agencies are employed in a paid job and only 15% were employed competitively. The proposed project will develop a product for school districts and higher education establishments to address the needs of approximately 8 million intellectually disadvantaged individuals in the United States education system. The implementation of this innovation seeks to impact the rates of employment in this population, resulting in increases in personal income, reduction of poverty levels, and better health outcomes for individuals. This Small Business Technology Transfer (STTR) Phase I project plans to create a scalable software framework which integrates, evaluates, and analyzes data from school districts and higher education programs in order to enable the use of machine learning to improve the relationship between transition intervention methods and employment outcomes. Using this innovation, school districts would be able accurately predetermine an individuals ability to successfully perform tasks associated with employment. Higher education programs which enroll adults with developmental disabilities may then effectively scale and develop an individuals employability skills. The framework will provide structured data collection, data alignment, and data interlinking for roadmaps which will be implemented into the product, enabling educators and individuals to interact, learning how employability programmatic factors and educator corrective actions contribute to employability skills development. 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.
NSF Program Director: Rajesh Mehta
| Status | Closed |
|---|---|
| Effective start/end date | 08/15/22 → 03/31/24 |
Funding
- STTR Phase I: $256,000.00
Active Fiscal Year
- FY2024
- FY2023
- FY2022
Start Fiscal Year
- FY2022
TIP Programs
- STTR Phase I
Small Business
- Yes
Key Technology Areas
- Artificial Intelligence
- (confidence score: 100%)
Technology Foci
- Machine Learning Training Data
- (confidence score: 93%)
Congressional District at Award
- District n. 06 of Louisiana
Current Congressional District
- District n. 06 of Louisiana
United States
- Louisiana
Core Based Statistical Area (CBSA)
- Baton Rouge, LA
County
- County: East Baton Rouge, LA
EPSCoR Jurisdiction
- Yes
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