Assessing the utility of a virtual reality arson crime scene investigation simulation
Bibliographic record
Abstract
Abstract This study examines the utility of a virtual reality (VR) arson crime scene investigation simulation developed by the Abu Dhabi Police service. Utilizing qualitative interviews with participants from the Saif Bin Zayed Academy for Security and Policing Sciences, the study captures views of the VR training experience with an emphasis on learning effectiveness, engagement, skill acquisition, cost and time efficiency, and inclusivity and accessibility. The findings are discussed in the context of a theoretical framework provided by the technology acceptance model (TAM) and indicate high levels of engagement and immersion among the participants. Many expressed a preference for VR training over classroom training. Thus, the ‘perceived usefulness’ of the technology was high. The interviewees also reported significant perceived benefits in terms of acquiring procedural knowledge and skills. The immersive nature of the VR was identified as a key factor in its utility. The cost and time efficiencies driven by the capability to train multiple officers simultaneously without the need for physical resources and with fewer of the risks commonly associated with live training are also outlined. The study also identified limitations regarding the inclusivity and accessibility of the technology, including among individuals with disabilities. Nevertheless, the overall reception of the simulation was positive. The findings indicate that VR is widely accepted within the police service and has great potential for wider use to enhance training in other areas if it serves to deliver content focused on policies and practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".