Participatory Design of Sonification Development for Learning about Molecular Structures in Virtual Reality
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
Background: Chemistry and biology students often have difficulty understanding molecular structures. Sonification (the rendition of data into non-speech sounds that convey information) can be used to support molecular understanding by complementing scientific visualization. A proper sonification design is important for its effective educational use. This paper describes a participatory design (PD) approach to designing and developing the sonification of a molecular structure model to be used in an educational setting. Methods: Biology, music, and computer science students and specialists designed a sonification of a model of an insulin molecule, following Spinuzzi’s PD methodology and involving evolutionary prototyping. The sonification was developed using open-source software tools used in digital music composition. Results and Conclusions: We tested our sonification played on a virtual reality headset with 15 computer science students. Questionnaire and observational results showed that multidisciplinary PD was useful and effective for developing an educational scientific sonification. PD allowed for speeding up and improving our sonification design and development. Making a usable (effective, efficient, and pleasant to use) sonification of molecular information requires the multidisciplinary participation of people with music, computer science, and molecular biology backgrounds.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it