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Record W4417190503 · doi:10.1080/00140139.2025.2595656

Training effectiveness and validation of a VR HMD-based simulator for air force pilots

2025· article· en· W4417190503 on OpenAlexaff
Ramy Kirollos, Wasim Merchant, Blake C. W. Martin, Jerzy Jarmasz, John Jong-Jin Kim

Bibliographic record

VenueErgonomics · 2025
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsVirtual realityTrainerFlight simulatorFlight trainingTraining (meteorology)Significant differenceTraining systemOverhead (engineering)

Abstract

fetched live from OpenAlex

Virtual reality (VR) head-mounted display (HMD) was examined for Air Force training modernisation. In Experiment 1 (E1), Novice pilots performed the Overhead break (OHB) manoeuvre and flight proficiency scores were measured and compared to Expert pilots OHB performance in a VR HMD-based simulator. Cybersickness was also measured. Experts performed significantly better on the OHB manoeuvre than Novices. Both groups improved significantly over the course of the experiment and cybersickness was negligible. E1 indicated that the VR HMD flight trainer can be valid, effective and safe for training the OHB maneuvre. Experiment 2 (E2) compared an established Flight Training Device (FTD; not the VR simulator) and Live Flight OHB scores for Novice pilots from E1 to Novices not in E1. There was no difference in FTD and Live Flight scores between both groups. E2 revealed that completion of E1 was insufficient to translate to superior performance in FTD and Live Flight.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.241
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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