Date of Award

3-2022

Document Type

Thesis

Degree Name

Master of Science in Cyber Operations

Department

Department of Electrical and Computer Engineering

First Advisor

Mark G. Reith, PhD

Abstract

Artificial Intelligence (AI) threatens to bring significant disruption to all aspects of military operations. This research develops a Serious Game (SG) and assessment methodology to provide education on the mindsets required for engaging with disruptive AI technologies. The game, Obsolescence, teaches strategic-level concepts recommended to the Department of Defense (DoD) from a compilation of reports on the current and future state of AI and warfighting. The methodology for assessing the educational value of Obsolescence addresses common challenges such as subjective reporting, control groups, population sizes, and measuring abstract or high levels of learning. The games proposed educational value is tested using a pre-and post-test format against a baseline established by official sources and experts in the fields of AI and strategic planning. The assessment includes metrics based on both self-reported learning and measurements of changes to participant responses to LO-related questions post-gameplay. The experiment found a strong correlation between the measured learning and participants' self-reported learning, and both metrics confirm that Obsolescence achieves its educational goals. This research includes the steps necessary to utilize the assessment methodology and presents recommendations both for Obsolescence and for future research in the field of educational game assessment.

AFIT Designator

AFIT-ENG-MS-22-M-039

DTIC Accession Number

AD1166900

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