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Record W3015126919 · doi:10.22215/etd/2020-13923

Examining the Effects of Perceived Telepresence, Interactivity, and Immersion on Pilot Situation Awareness During a Virtual Reality Flight Exercise

2020· dissertation· en· W3015126919 on OpenAlexaff
Cassandra Ommerli

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsCarleton University
Fundersnot available
KeywordsInteractivityVirtual realityImmersion (mathematics)AviationFlight simulatorHuman–computer interactionCognitionAffect (linguistics)Sense of presenceComprehensionMultimediaComputer scienceApplied psychologyEngineeringPsychologySimulation

Abstract

fetched live from OpenAlex

Flight simulators that use virtual reality (VR) displays are becoming more prevalent in the aviation domain, enabling situation awareness (SA) training and assessment paradigms that integrate a broad range of aircraft types and flight environments.Research has identified three key components of user psychological experiences during VR exposure that may affect cognitive performance: immersion, telepresence, and interactivity.The primary objective of this study was to validate and quantify the effects of these VR experience constructs on pilot SA at the levels of information processing and comprehension.Effects of age and experience were also explored, as these factors are known to influence achievement of SA.Findings from this research will provide insight into the ways in which pilots' psychological experiences of VR flight simulators affect their cognitive processing.Moreover, the results of this work will inform the design of improved VR systems for the training and assessment of pilot SA.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.354
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2020
Admission routes1
Has abstractyes

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