SBIR Phase I: AuthorIT: Authoring Adaptive and Configurable Tutoring Systems (A-ACTS)

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$100,000.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
0806858
Award Id:
88371
Agency Tracking Number:
0806858
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
1249 Greentree, Suite 100, Narberth, PA, 19072
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
788534969
Principal Investigator:
Joseph Scandura
PhD
(610) 664-1207
scandura@scandura.com
Business Contact:
Joseph Scandura
PhD
(610) 664-1207
scandura@scandura.com
Research Institution:
n/a
Abstract
This Small Business Innovation Research (SBIR) Phase I research project proposes a fundamentally new approach to knowledge representation and building highly Adaptive and Configurable Tutoring Systems (ACTS) based thereon. This authoring system, automates steps in knowledge representation, and eliminates the need to program pedagogical strategies and otherwise simplifies the process of building ACTS. An companion application automatically delivers learning as prescribed. This Phase I research aims to demonstrate the feasibility of: 1) using the technique to develop commercially-viable ACTS for well-defined STEM content; and 2) to extend the technique to support ACTS that will enable learners to solve novel problems that they have not been taught how to solve; and 3) to deliver such content over the web. Full realization of this innovation will increase the impact of ACTS in STEM education by increasing learning efficiency, reducing development costs, improving quality control and yielding systems that can easily be configured to meet specific educational needs. If successful, this project will result in ACTS having direct application in schools as well as open new opportunities in the commercial world. The application will cut development cost in half, making it commercially feasible to develop even specialized and highly efficient ACTS, while maintaining quality control, and has the potential of radically improving the way adaptive tutorial systems are built as well as the effectiveness of those systems.

* information listed above is at the time of submission.

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