Plotting a route to effective web-based avalanche education tools using geovisualization principles
Bibliographic record
Abstract
Interactive web-based avalanche tutorials are becoming increasingly popular in the avalanche community. However, the educational effectiveness of such novel interfaces is uncertain. This study explores properties of web-based interactive interfaces (representation, feedback, and single or multiple viewpoints) and their effect on amateur recreationists’ understanding and identification of avalanche hazards. An experimental exercise, incorporating the Canadian Avalanche Centre’s AVALUATOR booklet and a Flash-based interface based on its current training modules, was used to examine 172 participants’ responses to surveys measuring avalanche safety knowledge. The performance of a subset of participants on route-finding and hazard identification tasks was also examined. Survey scores increased significantly after the participants read the AVALUATOR booklet but not after the route-finding exercise. Participants correctly identified only 25% of visible hazards present on a single terrain photograph and route-finding worsened on successive attempts. Analysis suggests 2D representations and hazard feedback, delivered through Flash-based pop-ups, negatively impacted performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".