Instruction, modeling and simulation, virtual environment


Content augmentation strategies (CAS) are instructional methods which specify the overlaying of content objects by content augmentation objects in order to increase the effectiveness and efficiency of instruction. The goals of this research were to build a comprehensive framework around CASs, determine the experimental effects of CASs in an instructional virtual environment (VE), and make recommendations regarding the employment and further study of CASs in instructional virtual environments. The VE experiment examined the effectiveness and efficiency impact of six different content augmentation strategies which overlayed different content augmentation objects onto four immersive VE scenarios. Sixty university students, 40 men and 20 women, executed three CAS-enhanced training missions and one no-CAS test mission. The task involved the recall and correct application of specific rules for three subtasks of a military helicopter landing zone scouting mission. The strategies included a no-strategy control condition, an arrow condition, an audio coaching condition, a text coaching condition, an arrow plus audio coaching condition, and an arrow plus text coaching condition. Statistical and decision analyses were conducted on the effectiveness and efficiency performance data. Statistically significant differences were found which supported the general superiority of the audio content augmentation strategy for these tasks. This dissertation may be the first use of a decision analysis approach for analyzing the results of behavioral data for instructional design decisions. The decision analysis approach used decision trees, simulation and optimization to obtain content augmentation strategy rankings. As this approach is normally used for course of action analysis and comparing alternative system configurations, the validity of this approach in this context has yet to be determined. The decision analysis approach obtained plausible and similar, but not identical recommendations to the statistical approach. The decision analysis approach may constitute a limited instantiation of a proposed optimal stimulus set instructional design model which conceptually framed the experiment. Training guideline recommendations, experimental procedure recommendations, and a comprehensive framework for future research are also presented.


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Graduation Date





Kincaid, J. Peter


Doctor of Philosophy (Ph.D.)


College of Arts and Sciences

Degree Program

Modeling and Simulation








Release Date

January 2007

Length of Campus-only Access


Access Status

Doctoral Dissertation (Open Access)