Higher Automated Learning (HAL II)

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$500,000.00
Award Year:
2013
Program:
SBIR
Phase:
Phase II
Contract:
N00014-12-G-05460011
Award Id:
n/a
Agency Tracking Number:
O113-CR1-4093
Solicitation Year:
2011
Solicitation Topic Code:
OSD11-CR1
Solicitation Number:
2011.2
Small Business Information
12 Gill Street, Suite 1400, Woburn, MA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
967259946
Principal Investigator:
Alan Carlin
Senior Research Engineer
(781) 496-2444
acarlin@aptima.com
Business Contact:
Thomas McKenna
Chief Financial Officer
(781) 496-2443
mckenna@aptima.com
Research Institution:
n/a
Abstract
The United States Marine Corps (USMC) has recognized the need for better decision making among leaders at all levels, especially among small unit leaders. In response to this the Office of Naval Research has begun a program of training research and development for Accelerated Development of Small Unit Decision Making (ADSUDM). This is a significant undertaking. In this document, Aptima proposes to develop and apply Higher Automated Learning (HAL) Phase II as a research accelerator for ADSUDM. HAL is a data mining approach that generates trainee assessments based on previous training data. It consists of a three part mathematical model to assess student progress. Principal Component Analysis identifies the knowledge components being trained and the training objectives. Hidden Markov Models assess progress along the trainee learning path. Item Response Theory produces a direct measure of trainee performance, and also identifies the difficulty of each training item. When completed, HAL will allow trainees to learn faster and retain knowledge longer, and it will allow instructors to make better feedback and remediation decisions. HAL will also help institutions reduce the costs of implementing the design and evaluation process.

* information listed above is at the time of submission.

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