The Impact of Night Vision Goggles on Way-Finding Performance and the Acquisition of Spatial Knowledge
Bibliographic record
Abstract
OBJECTIVE: This study examined the effects of night vision goggles (NVGs) on navigation and way-finding performance and the acquisition of spatial knowledge. BACKGROUND: Although numerous studies have examined the effects of NVGs on visual perception, few have examined the effects of using NVGs on the acquisition and expression of spatial cognition. METHOD: Participants learned the environment through active navigation and way finding, searching for targets within a life-sized maze with or without NVGs. Knowledge of the environment was then tested with two spatial memory tests. RESULTS: Findings show that navigation and way finding with NVGs appear to be harder, as indicated by longer navigation times and additional, unnecessary turns, than they are without NVGs. Moreover, change in navigation performance over the course of the way-finding trials varied as a function of group assignment indicating that NVGs influenced the learning process. NVG users demonstrated a significant decrease in navigation times earlier as well as significant decreases in navigational legs compared with the control group. In judging the positions of objects relative to target objects in different rooms in the maze, performance was better for participants without NVGs than for those with NVGs. In a map-drawing task, participants in the NVG group were more likely to position objects incorrectly and to receive worse scores than the controls. CONCLUSION: These results demonstrate that NVGs affected not only spatial navigation and way-finding performance but also the acquisition of spatial knowledge. APPLICATION: These degradations in spatial knowledge should be considered in operational planning and NVG training programs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".