A Mixed-Method Analysis of Usability Study of Video and VR Safety Training: Towards Implementation of VR in Working at Height Training
Bibliographic record
Abstract
Falling from height is considered one of the top causes of workplace injuries and fatalities in the construction industry.The regulatory WAH training, conducted in-class and lecture-based, has been successfully implemented; however, its effect is modest.This study aims to find the relationship between the traditional method and VR simulation in terms of user perception.A crossover design was adopted where participants experienced video and VR training in different sequences.Widely used SUS to measure perceived usability and a VR perception questionnaire was implemented.The two-factor analysis of SUS resulted in new usability and learnability.The result shows no significant difference in perceived usability between the training methods.However, on further analysis, one group found video easier to learn.Similarly, there was a significant inclination of users towards VR training in terms of preference, engagement, and ease of remembering.The Spearman correlation revealed older participants perceived the VR interface as less usable.It was also observed that the training order with video first followed by VR perceived the overall system better as compared to the other group.Further suggestions using qualitative data analysis are proposed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".