Changing Perspectives: Enhancing Learning Efficacy with the After-Action Review in Virtual Reality Training for Police 5 107 experienced team leaders and police officers may have had a different learning experience and thus learning efficacy than teams of different compositions (Paoline III & Terrill, 2007). In addition, gender of police officers may also influence learning efficacy. For instance, female police officers experience differences in operational task assignments (Rabe-Hemp, 2009; Morash & Haarr, 2012) and thus may take unfavorable roles in team compositions, reducing their learning efficacy. CONCLUSIONS In conclusion, the AAR appears to be a promising feature of VR and provides police agencies with feedback opportunities that are difficult to simulate in real-life training (Murtinger et al., 2021). Reviewing training performance from various perspectives and utilizing additional features to underscore performance makes the AAR an effective training tool that supports police instructors when giving feedback. To further enhance the use of the AAR in practice, police agencies should aim to identify AAR features that align with the learning objective of the training when setting up the VR training (Bennell et al., 2020). For instance, when trainees are tasked with clearing and searching various rooms, police instructors may utilize AAR features such as the walking routes the officers took, and display of gaze areas that were covered. In the AAR, the instructors and trainees can then review and compare which paths they took to clear a room, the areas their gaze covered, and whether the strategies to conduct a clearance changed from room to room. Similarly, instructors should avoid using AAR features that do not align with the training and learning objective. For example, during a training aimed at verbal de-escalation or taking cover to observe a suspects’ behavior (i.e., a training that has no intention to rely on the service weapon), showing the line of fire would distract from the objective of the training. Thus, utilizing too many features provides trainees with information that may not be relevant to them or the purpose of the training (Bennell et al., 2020). VR providers can further support the implementation of AAR in police practice by developing context-specific review features. For instance, next to enabling trainees to view their performance from a first-person perspective and a suspect perspective, features such as showing the hit zones after using a service weapon may be relevant performance indicators. VR providers for police training should therefore consider developing these context-specific features in collaboration with police instructors. Lastly, to make the debrief process efficient and effective, VR providers should design an accessible AAR tool that makes it easy for police instructor to select and use the relevant features during the debrief. Because “feedback is one of the most powerful influences on learning” (Hattie & Timperley, 2007), designing and implementing VR AAR effectively in police training can enhance the delivery of feedback and subsequently improve learning and performance of police officers.
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