Fostering large display engagement through playful interactions
Bibliographic record
Abstract
Challenges confronting designers of public displays include display blindness, i.e. the propensity of people to ignore these displays as they become ever-more ubiquitous, and the "first click" problem, i.e. users not interacting with these displays due to being unaware of interactive content. To address the challenge of display blindness, explicit and tacit mechanisms for interacting with displays have been explored. Unfortunately, because of the short-term nature of many installations, it has been difficult both to assess the relative effects of different interventions because of limited statistical power and to assess the relative effects of different interventions due to display blindness because the short-term nature of deployment limits the onset of display blindness. We explore two simple whole body (non-touch) interactions with a public display, one a user skeleton and the second a simple game, to explore their relative efficacy at capturing passers-by attention and at keeping passers-by engaged. We demonstrate the complimentary benefits of user-shadowing and playful tasks as a mechanism to both capture and keep in the context of public deployments.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".