Design Principles for VanVR APP: a Virtual Anatomy Lab
Bibliographic record
Abstract
The VanVR APP (Vancouver Virtual Reality Anatomy and Pathology Project) is a virtual anatomy lab with 3D anatomy dissection scans, which in the post‐pandemic learning environment is a “digital twin” to the physical lab. The principles of this re‐design are based on instructors' need to offer an alternate supplemental teaching environment, and students’ need to access high‐quality anatomy scans preparing for the dissection lab experience. VanVR was created using Unity and WebGL offering two separate user interfaces (UI): one for students and one for instructors. The student UI leads to a virtual anatomy lab (VAL) of interactive 3D models. The instructor UI; the Lab Maker (LM), allows instructors to customize their courses from a wide database of fully‐labeled specimens, images, and videos. VanVR’s user experience (UX) of the VAL was designed to mimic a lab’s environment including anatomy code of conduct and many control functions. UI and UX designs intend to meet student needs with a focus on intuitive interfaces and interactions to maximize attention on the anatomy content rather than navigating technological difficulties. VanVR was designed as an accessible web app using a traditional and universal design layout that allows for seamless future mobile/tablet expansion. In the student portal and the LM, organized by importance, the main bulk of the course material was centrally placed in common sections to allow for an effective tree hierarchy and smooth accessibility. The student UI visual hierarchy was highlighted via a checklist to track weekly learning progress supplemented by course material, lab manuals, specimens, videos, and images. The login information, content menu, and sub‐menus were then distributed around the main grid. This layout helped to convey easy navigation, accessibility, and uniform connectivity. The anatomy content menu was sorted by body regions (atlas or textbook hierarchy). The aim of VanVR's layout was to mimic familiar apps for a smooth user experience. Moreover, to attain user seamless transition, VanVR’s layout matched UBC’s learning management system; Canvas features such as student checklists, content upload, and editing course material in the LM. Equal principles were used in the UX, the VAL design resembles an actual anatomy lab, this mimicry principle induces learnability. The user control shows the main elements in a simple hierarchy, design, colors, and text font granting intuitive and seamless navigation. To deliver flexibility and redundancy, we added multiple logical routes to finish tasks and bypass system lags. For more student‐instructor interaction, instructors were given the feature to control the number of labels on the specimens or pose question labels to match the learning objectives. As a result, VanVR UI and UX design followed basic aesthetics aiming for an efficient and accessible learning/teaching tool. Our future plan includes adapting the UI and UX to smartphone/tablet screen size and features. For more accessibility and redundancy, a search feature will be added to allow users to rapidly find specimens.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".