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SCALE: Making EdTech Products Adaptive and Personalized for Improved Training and Education

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8751-19-P-A033
Agency Tracking Number: F191-005-1190
Amount: $50,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF191-005
Solicitation Number: 19.1
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-03-06
Award End Date (Contract End Date): 2019-06-04
Small Business Information
505 Linden Ct
Mars, PA 16046
United States
DUNS: 967553566
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Mary Jean Blink
 Principal Investigator / Chief Operating Officer
 (513) 378-1668
Business Contact
 John Stamper
Phone: (704) 701-8445
Research Institution

TutorGen’s Student Centered Adaptive Learning Engine (SCALE®) is a commercially mature EdTech product that represents a breakthrough in developing adaptive educational systems. SCALE collects data from any new or existing computer/web based training software, and uses educational data mining and artificial intelligence techniques to automatically generate intelligent tutoring capabilities. SCALE builds and improves student and problem-set models over time as more data is collected, and tracks student progress on specific concepts or skills (knowledge tracing). This allows for easy assessment at any point in time. The system also dynamically selects the next best problem to maximize student learning and minimize time needed to master a set of skills (problem selection). For complex, multi-step problems, SCALE can provide context specific, just-in-time hints. SCALE also provides data adapters so edtech developers can easily hook into the SCALE system using Web APIs. Finally, a main differentiator of our system is our transparent process of data curation and the related visual tools that expose the workings of the problem and student-model generation process. By building on award-winning learning science and data mining research, we have designed and developed a learning engine that makes adding adaptive capabilities to existing systems easy and affordable.

* Information listed above is at the time of submission. *

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