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AN AUTOMATED TRAINING SYSTEM FOR BUILDING EXPERTISE

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
8487
Program Year/Program:
1988 / SBIR
Agency Tracking Number:
8487
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Decision Science Associates
P.O. Box 969 Vienna, VA 22183 0096
View profile »
Woman-Owned: No
Minority-Owned: Yes
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 1988
Title: AN AUTOMATED TRAINING SYSTEM FOR BUILDING EXPERTISE
Agency / Branch: DOD / USAF
Contract: N/A
Award Amount: $59,975.00
 

Abstract:

COMPUTER-BASED TUTORIAL SYSTEMS HAVE NOW BECOME EFFECTIVE TRAINERS IN A NUMBER OF DOMAINS. MANY GOOD SYSTEMS ARE MODELED AFTER THEORIES OF HUMAN LEARNING AND KNOWLEDGE REPRESENTATION. HOWEVER, SUCH SYSTEMSTYPICALLY ASSUME A LIMITED VIEW OF HUMAN KNOWLEDGE, HENCE LIMITING THEIR APPLICABILITY TO INTRODUCTORY LEVEL MATERIAL. RESEARCH BY THE PROPOSED PROJECT TEAM HAS SHOWN THAT EXPERTS HAVE A BROAD RANGE OF KNOWLEDGE STRUCTURES. ANY TRAINING SYSTEM (COMPUTER OR OTHER) ATTEMPTING TO BUILD STUDENT'S EXPERTISE SHOULD GUIDE ITS INSTRUCTION ACCORDING TO HOW EXPERTS REPRESENT AND USE KNOWLEDGE. WE PROPOSE TO BUILD A COMPUTER-BASED TRAINING SYSTEM AND OVERALL TRAINING METHODOLOGY THAT HELPS STUDENTS INTEGRATE A WIDE RANGE OF KNOWLEDGE (E.G., PLANNING, CAUSAL REASONING, CONCEPT FAMILIARITY) AND APPLY IT TO PRACTICAL PROBLEMS. IN ADDITION, WE PROPOSE TO USE KNOWLEDGE ELICITATION TECHNIQUES DEVELOPED BY THE PROPOSED PROJECT TEAM TO EVALUATE THE EFFECTIVENESS OF TRAINING AND GUIDE CORRECTIVE INSTRUCTION.

Principal Investigator:

John leddo
7036200660

Business Contact:

Small Business Information at Submission:

Decision Science Consortium
1895 Preston White Dr - Ste 30 Reston, VA 22091

EIN/Tax ID:
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No