Abstract & Details
Description
Award ID: 2151406
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a scalable, on-demand, research-based innovation for learners in virtual and recorded training programs. Research has shown that underrepresented populations arrive at an undergraduate institution less likely to have the advanced study skills or confident awareness to seek assistance when faced with uncertainty in the classroom. This project provides on-demand responses to in-lesson queries and helps develop deep study skills. Additionally, for the students who arrive at college without sufficient familial or academic support, the proposed product becomes a resource to participate successfully in an undergraduate environment. This Small Business Innovation Research (SBIR) Phase I project will build an engine that automatically identifies the discipline of a course based on the extracted words and phrases spoken or visually presented in class, and then will identify terms important to the learning objectives of the course, garnered via categorical arrays of discipline specific keywords. Automatic creation of personalized study guides is initiated based on the learners' individual queries or class discussions. This innovation is applicable to the remote learning industries, where it may increase the value of their customers online content and enable teaching professionals to strive for higher levels of equity in the student population. 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 Innovation Research (SBIR) Phase I project is to develop a scalable, on-demand, research-based innovation for learners in virtual and recorded training programs. Research has shown that underrepresented populations arrive at an undergraduate institution less likely to have the advanced study skills or confident awareness to seek assistance when faced with uncertainty in the classroom. This project provides on-demand responses to in-lesson queries and helps develop deep study skills. Additionally, for the students who arrive at college without sufficient familial or academic support, the proposed product becomes a resource to participate successfully in an undergraduate environment. This Small Business Innovation Research (SBIR) Phase I project will build an engine that automatically identifies the discipline of a course based on the extracted words and phrases spoken or visually presented in class, and then will identify terms important to the learning objectives of the course, garnered via categorical arrays of discipline specific keywords. Automatic creation of personalized study guides is initiated based on the learners' individual queries or class discussions. This innovation is applicable to the remote learning industries, where it may increase the value of their customers online content and enable teaching professionals to strive for higher levels of equity in the student population. 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 | 01/15/23 → 12/31/23 |
Funding
- SBIR Phase I: $256,000.00
Active Fiscal Year
- FY2024
- FY2023
Start Fiscal Year
- FY2023
TIP Programs
- SBIR Phase I
Small Business
- Yes
Key Technology Areas
- Artificial Intelligence
- (confidence score: 99%)
Technology Foci
- Artificial Intelligence (excluding ML)
- (confidence score: 95%)
Congressional District at Award
- District n. 01 of Michigan
Current Congressional District
- District n. 01 of Michigan
United States
- Michigan
Core Based Statistical Area (CBSA)
- Traverse City, MI
County
- County: Leelanau, MI
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