ORCID

0009-0003-7297-5894

Keywords

Scenario Based Training, Law Enforcement Training, Virtual Simulation Training, Environmental Fidelity, Presence and Agency, Cognitive Affective Model of Immersive Learning (CAMIL)

Abstract

Realistic scenario based training (SBT) is an effective method used to prepare police officers for real world use of force incidents. Many law enforcement agencies are unable to host regular SBT due to time, cost, and facility constraints. A novel simulation training approach was investigated to determine if it may be a suitable alternative or supplement to traditional SBT at reduced cost, time, and increased frequency. This novel scenario based simulation training (SBST) environment combined physical and virtual elements into a single training scenario. A physical space, designed to depict the scene of a critical incident, was equipped with immersive technological factors including interactive virtual human avatars. A mixed-methods, within-subjects, counterbalanced design was adopted to measure performance, sense of presence, and sense of agency between a traditional low fidelity shoot house control condition and a high fidelity, open scenario based simulation training condition among a sample of 15 police recruits. The SBST condition produced significantly higher feelings of presence, attempts to employ de-escalation techniques, and use of cover. Marksmanship performance deteriorated in the SBST condition. Participants fired more shots and missed at a higher frequency than the shoot house condition. The sense of agency was unchanged between conditions. The findings suggest that there is some evidence that the Cognitive Affective Model of Immersive Learning (CAMIL), a theoretical framework for learning and training in immersive virtual environments, may generalize to this domain. The results suggest that high fidelity, open SBST for law enforcement training may effectively simulate real critical incidents and provide a venue to train policing skills. Further research with a larger, more experientially diverse sample of law enforcement professionals is necessary to increase confidence in these findings.

Completion Date

2025

Semester

Spring

Committee Chair

Maraj, Crystal

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

School of Modeling, Simulation and Training

Identifier

DP0029334

Document Type

Dissertation/Thesis

Campus Location

Orlando (Main) Campus

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