Establishing a Coding System for Use of Force Encounters to Develop an Immersive Training Model
Faculty Mentor Name
Diana Orem
Format Preference
Poster
Abstract
Modern day policing demands have expanded the scope of the types of individuals and situations law enforcements officers (LEOs) must be trained to handle. The current reality is that several issues hamper the potential for improvement: 1) inconsistent training; 2) inconsistent tracking; 3) not enough training, not mandatory, no follow-up 4) differences in populations that fall under this broad umbrella. Thus, it is imperative that new trainings methods are not only developed to accommodate these needs, but also be effective and feasible for LE agencies. We propose a novel method of determining why and how encounters between neurodivergent and LE go poorly, and in extreme cases, end in the death of the individual. In the Spring term, we will do this by cataloging known cases, locating the bodycam footage if it is available, and developing a coding system for analyzing the encounter. Due to restrictions of footage, we will pull data from any use of force encounters we have access to. Validity and interrater reliability will be assessed and training will continue until satisfactory criteria are met. Once this process is complete, data will be analyzed to determine which types of errors are most frequent and which are most likely to lead to undesirable outcomes. For the Summer term, we will translate the data into an interactive, simulation-based training protocol where trainees will interact with real footage and receive constructive feedback in real-time. Adapt Showcase, an online course building software, will be used to create a new training that analyzes critical points throughout an officer's interaction with an autistic individual. The goal is to pilot this training through an existing autism and LE curriculum. The outcomes hope to address the pressing need to provide training to members of LE on how to interact safely with autistic individuals in their communities.
Establishing a Coding System for Use of Force Encounters to Develop an Immersive Training Model
Modern day policing demands have expanded the scope of the types of individuals and situations law enforcements officers (LEOs) must be trained to handle. The current reality is that several issues hamper the potential for improvement: 1) inconsistent training; 2) inconsistent tracking; 3) not enough training, not mandatory, no follow-up 4) differences in populations that fall under this broad umbrella. Thus, it is imperative that new trainings methods are not only developed to accommodate these needs, but also be effective and feasible for LE agencies. We propose a novel method of determining why and how encounters between neurodivergent and LE go poorly, and in extreme cases, end in the death of the individual. In the Spring term, we will do this by cataloging known cases, locating the bodycam footage if it is available, and developing a coding system for analyzing the encounter. Due to restrictions of footage, we will pull data from any use of force encounters we have access to. Validity and interrater reliability will be assessed and training will continue until satisfactory criteria are met. Once this process is complete, data will be analyzed to determine which types of errors are most frequent and which are most likely to lead to undesirable outcomes. For the Summer term, we will translate the data into an interactive, simulation-based training protocol where trainees will interact with real footage and receive constructive feedback in real-time. Adapt Showcase, an online course building software, will be used to create a new training that analyzes critical points throughout an officer's interaction with an autistic individual. The goal is to pilot this training through an existing autism and LE curriculum. The outcomes hope to address the pressing need to provide training to members of LE on how to interact safely with autistic individuals in their communities.