Adaptive, individualized training assessment capability (AITAC)

Award Information
Agency:
Department of Defense
Branch
n/a
Amount:
$149,918.00
Award Year:
2012
Program:
SBIR
Phase:
Phase I
Contract:
N00014-12-M-0248
Award Id:
n/a
Agency Tracking Number:
O113-CR1-4053
Solicitation Year:
2011
Solicitation Topic Code:
OSD11-CR1
Solicitation Number:
2011.3
Small Business Information
3600 Green Court, Suite 600, Ann Arbor, MI, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
009485124
Principal Investigator:
RobertWray
Senior Scientist
(919) 967-5079
wray@soartech.com
Business Contact:
AndrewDallas
Vice President, Federal Systems
(734) 887-7603
contracts@soartech.com
Research Institute:
Stub




Abstract
The revolution in simulation and virtual technologies for training is enabling learners to practice skills and learn in realistic environments. Researchers are also seeking to develop algorithms that can tailor learner practice to the estimated abilities and needs of individual students, offering the promise of individual adaptation to each learner"s dynamically evolving zone of proximal development. Such systems will likely improve learning outcomes, reduce learner frustration, and mitigate the need for artificial (out of domain) scaffolding. However, such adaptive training requires that a learning environment estimate student proficiency and need as learning progresses and most approaches assume that the primary assessment dimensions are known in advance, which limits the ultimate effectiveness of adaptive training systems. What would be preferable is the ability of the system to assess progress and stumbling blocks within the environment and diagnosis and measure these deficits in terms of dimensions"outside"of the a priori trainee representation. We propose a direct questioning approach, building on domain ontologies and prior work in machine learning of student proficiency modeling, along with dynamic assessment and tailoring, to build a more accurate and more extensible representation of individual trainees.

* information listed above is at the time of submission.

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