Interactive Tables in the Wild - Visitor Experiences with Multi-Touch Tables in the Arctic Exhibit at the Vancouver Aquarium
Bibliographic record
Abstract
This report describes and discusses the findings from a field study that was conducted at the Vancouver Aquarium to investigate how visitors explore and experience large horizontal multi-touch tables as part of public exhibition spaces. The study investigated visitors’ use of two different tabletop applications—the Collection Viewer and the Arctic Choices table—that are part of the Canada’s Arctic exhibition at the Vancouver Aquarium. Our findings show that both tabletop exhibits enhanced the exhibition in different ways. The Collection Viewer table evoked visitors curiosity by presenting visually interesting information and engaged by supporting lightweight, playful, and open-ended information exploration. The Arctic Choices table enabled visitors to explore a variety of information about environmental and political changes within the Arctic in depth by providing detailed data visualizations. The application triggered a lot of insightful discussions among visitors. Our study findings include a discussion of the factors that attracted visitors’ attention and triggered interaction with both tabletop exhibits, the character and duration of information exploration, general exploration strategies, and factors that triggered social and collaborative information exploration. We also discuss usability issues of both tabletop applications alongside possible solutions.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".