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Record W1699323578 · doi:10.21432/t22s5f

Does Simulator Sickness Impair Learning Decision Making While Driving a Police Vehicle? | Le mal du simulateur: un frein à l’apprentissage de la prise de décision en conduite d’un véhicule de police?

2015· article· fr· W1699323578 on OpenAlexaffvenueabout
Eve Paquette, Danielle-Claude Bélanger

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2015
Typearticle
Languagefr
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsMontreal Police ServiceUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPsychologyHumanitiesSession (web analytics)ArtComputer science

Abstract

fetched live from OpenAlex

The use of driving simulators is an innovation for police training in Quebec. There are some issues related to their impact on training objectives. This article presents the results of a study involving 71 police cadets who participated in six training sessions with a driving simulator. The training sessions were designed to competencies development to make decisions during emergency driving and pursuit. The nature and consequences of the discomfort experienced by the participants is described. The results highlight the importance of the initial training session. Issues related to providing trainees with adequate support are discussed. Le simulateur de conduite est un outil pédagogique novateur pour la formation policière au Québec. Il comporte des enjeux à l’égard de l’atteinte des objectifs pédagogiques visés. L’article présente les résultats d’une recherche menée auprès de 71 aspirants policiers ayant participé à une formation de six séances au simulateur de conduite visant le développement des compétences en matière de prise de décision en conduite d’urgence et en poursuite. Les résultats dressent un portrait des malaises ressentis par les participants et de leurs impacts. Les résultats montrent également l’importance de la première séance. La discussion s’attarde aux enjeux liés à l’accompagnement des apprenants.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.304
Teacher spread0.295 · 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.

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
Published2015
Admission routes3
Has abstractyes

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