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High-level tools and languages for faster Intelligent Tutoring System(ITS) model development

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-11-M-0362
Agency Tracking Number: N11A-032-0147
Amount: $149,919.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N11A-T032
Solicitation Number: 2011.A
Timeline
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-06-27
Award End Date (Contract End Date): N/A
Small Business Information
3600 Green Court Suite 600
Ann Arbor, MI -
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Brian Stensrud
 Research Scientist
 (407) 207-2237
 stensrud@soartech.com
Business Contact
 van Lent
Title: President
Phone: (734) 887-7601
Email: contracts@soartech.com
Research Institution
 University of Southern California
 Amechi Akpom
 
12015 Waterfront Drive
Playa Vista, CA 90094-2536
United States

 (310) 448-0355
 Nonprofit College or University
Abstract

Intelligent tutoring systems (ITSs) hold the promise of dramatically increasing the cost effectiveness of training. However, one contributor to the per-lesson cost effectiveness of ITSs is the significant effort that goes into creating instructional material. ITSs in many ways shift the costs of giving instruction to the costs of preparing instruction. Preparation costs generally are quite high. In spite of ITSs being generally successful and mature technology, the DoD in general and the US Navy in particular have been hesitant to adopt it. There are three significant properties of the state of the art that contribute to this situation: domain specificity, domain unsuitability, and the high cost of instruction preparation. SoarTech, together with the Institute for Creative Technologies (ICT), will address these issues with the FACITS (Fast Authoring of Content for Intelligent Tutoring Systems) design study to investigate, develop, and evaluate ITS authoring tools that will provide general and reusable authoring abstractions, support dynamic and ill-defined training domains, and significantly reduce the cost of authoring new instructional material.

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

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