Date of Award

2011

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Systems Engineering

First Advisor

Ntuen, Celestine A. Dr.

Abstract

This thesis presents the application of a finite state automaton (FSA) to analytic modeling of Data/Frame Model (DFM) of sensemaking. A FSA is chosen for the DFM simulation because of its inherent characteristics to mimic changes in system behaviors and transitional states akin to the dynamic information changes in dynamic and unstructured emergencies. It also has the ability to capture feedback and loops, transitions, and spatio-temporal events based on iterative processes of an individual or a group of sensemakers. The thesis has exploited the human-driven DFM constructs for analytical modeling using Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) software system. Sensemaking times, problem stage time (PST), and nodeto-node (NTN) transition times serve as the major performance factors. The results obtained show differences in sensemaking times based on problem complexity and information uncertainty. An analysis of variance (ANOVA) statistical analysis, for three developed fictitious scenarios with different complexities and Hurricane Katrina, was conducted to investigate sensemaking performance. The results show that sensemaking performance was significant with an F (3,177) of 16.78 and probability value less than 0.05, indicating an overall effect of sensemaking information flow on sensemaking. Tukey’s Studentized Range Test shows the significant statistical differences between the complexities of Hurricane Katrina (HK) and medium complexity scenario (MC), HK and low complexity scenario (LC), high complexity scenario (HC) and LC, and MC and LC.

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