Novice Learner Driver Perceptions of the Efficiency of Driving Simulator-Based Training in a Natural Setting in Quebec
Bibliographic record
Abstract
Novice, adolescent driver overrepresentation in road crashes is a well-documented, robust phenomenon. Driver education and training are popular but controversial interventions that have rarely demonstrated safety benefits. Flight simulators have proven effective in pilot training and the decreasing costs and increasing quality of simulation technology make driving simulator-based training (DSBT) more feasible. In 2010, a long-term, naturalistic, transfer-of-training (ToT) study began to examine the effectiveness of substituting DSBT for part of the on-road training. Within the ToT study, one driving simulator hour can replace one on-road hour for up to 50% of the 15 hours of mandatory on-road lessons. The final results of the ToT study, due in 2015, will address two main questions. One, how does DSBT compare with on-road instruction in terms of performance on the government road exam? Two, does DSBT affect adolescent driver safety? This article presents questionnaire data from the first cohort of graduate learner drivers who substituted at least one hour of on-road training with one driving simulator hour. The questionnaires address learners’ general perceptions of learning to drive and their specific perceptions of DBST and its comparative efficiency to on-road training as well as driving teachers’ perceptions of their learners’ driving competence. Results indicate that DSBT compared favorably with on-road lessons and is perceived to be either more efficient than or equally efficient to on-road lessons for 13 of 15 specific driving skills. In addition, driving teachers gave their learners high competency ratings.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".