MoleculAR: An Augmented Reality Application for Understanding 3D Geometry
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide MoleculAR is a free, multiplatform augmented reality (AR) application that allows students to visualize and manipulate molecular structures in 3D, providing a more immersive and interactive learning experience. Using QR codes to generate 3D models of molecules, geometries, and orbitals, students can explore structures in real-time using their smartphones or tablets. Based on student survey responses, the app is effective at engaging students in both first- and second-year chemistry courses. Our goals for MoleculAR include providing a universally accessible tool for students to learn about molecular geometry and allowing for instructor adaptation and customization to make it as relevant as possible for individual courses. The skills students develop with the help of the app are highly transferable to other topics or areas, making it a valuable resource for educators in other fields. We welcome other educators to adopt the app to facilitate their teaching and improve the learning outcomes for their students.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".