Development of a Web-Based 3D Module for Enhanced Neuroanatomy Education.
Bibliographic record
Abstract
Neuroanatomy is a challenging subject, with novice medical students often experiencing difficulty grasping the intricate 3D spatial relationships. Most of the anatomical teaching in undergraduate medicine utilizes conventional 2D resources. E-learning technologies facilitate the development of learner-centered educational tools that can be tailored to meet each student's educational needs, and may foster improved learning in neuroanatomy, however this has yet to be examined fully in the literature. An interactive 3D e-learning module was developed to complement gross anatomy laboratory instruction. Incorporating such 3D modules may provide additional support for students in areas of anatomy that are spatially challenging, such as neuroanatomy. Specific anatomical structures and their relative spatial positions to other structures can be clearly defined in the 3D virtual environment from viewpoints that may not readily be available using cadaveric or 2D image modalities. Providing an interactive user interface for the 3D module in which the student controls many factors may enable the student to develop an improved understanding of the spatial relationships. This work outlines the process for the development of a 3D interactive module of the cerebral structures included in the anatomy curriculum for undergraduate medical students in their second year of study.
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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 | 0.000 | 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 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".