Development of an Approach for Multi-axis Assessment for Diagnosticity Enhancement in Individualized Training (MADE-IT)

Award Information
Agency:
Department of Defense
Amount:
$149,650.00
Program:
SBIR
Contract:
N00014-12-M-9246
Solitcitation Year:
2011
Solicitation Number:
2011.3
Branch:
Navy
Award Year:
2012
Phase:
Phase I
Agency Tracking Number:
O113-CR1-4060
Solicitation Topic Code:
OSD11-CR1
Small Business Information
Design Interactive, Inc.
1221 E. Broadway, Suite 110, Oviedo, FL, -
Hubzone Owned:
N
Woman Owned:
Y
Socially and Economically Disadvantaged:
Y
Duns:
075104708
Principal Investigator
 Meredith Carroll
 Sr Research Associate II
 (407) 706-0977
 meredith@designinteractive.net
Business Contact
 John Stanney
Title: Sr VP Finance
Phone: (407) 706-0977
Email: john@designinteractive.net
Research Institution
N/A
Abstract
Design Interactive (DI) proposes the Multi-axis Assessment for Diagnosticity Enhancement in Individualized Training (MADE-IT). MADE-IT will be a trainee model development approach and software tool that will support a user in developing a domain-specific individualized trainee model for integration into an ITS. MADE-IT will enhance current trainee modeling approaches in the following by 1) incorporating a domain-specific performance ontology that will: represent domain knowledge, reason about the elements and relations of that domain, support evaluation of performance and interpretation of data and provide scoring models and criteria for performance, 2) layering on affective state metrics of the learner to understand how emotions, moods, and attitudes are playing into performance and learning, 3) layering on cognitive state metrics of the learner to understand how cognition and limitations are affecting learning and performance, 4) factoring in individual traits that affect learning, such as learning styles and self-esteem, and 5) utilizing a machine learning agent make inferences and predictions about trainee knowledge, skills and learning based on available (and potentially limited) performance and physiological data.

* information listed above is at the time of submission.

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