Visualizing biological data in museums: Visitor learning with an interactive tree of life exhibit
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In this study, we investigate museum visitor learning and engagement at an interactive visualization of an evolutionary tree of life consisting of over 70,000 species. The study was conducted at two natural history museums where visitors collaboratively explored the tree of life using direct touch gestures on a multi‐touch tabletop display. In the study, 247 youth, aged 8–15 years, were randomly assigned in pairs to one of four conditions. In two of the conditions, pairs of youth interacted with different versions of the tree of life tabletop exhibit for a fixed duration of 10 minutes. In a third condition, pairs watched a 10 minute video on a similar topic. Individual responses on a 53‐item exit interview were then compared to responses from a fourth, baseline condition. Contrasting with the baseline condition, visitors who interacted with the tabletop exhibits were significantly more likely to reason correctly about core evolutionary concepts, particularly common descent and shared ancestry. They were also more likely to correctly interpret phylogenetic tree diagrams. To investigate the factors influencing these learning outcomes, we used linear mixed models to analyze measures of dyads’ verbal engagement and physical interaction with the exhibit. These models indicated that, while our verbal and physical measures were related, they accounted for significant portions of the variance on their own, independent of youth age, prior knowledge, and parental background. Our results provide evidence that multi‐touch interactive exhibits that enable visitors to explore large scientific datasets can provide engaging and effective learning opportunities. © 2016 Wiley Periodicals, Inc. J Res Sci Teach 53: 895–918, 2016
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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 | 0.027 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it