Learning in Stereo: The Relationship Between Spatial Ability and 3D Digital Anatomy Models
Why this work is in the frame
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Bibliographic record
Abstract
Three‐dimensional (3D) digital anatomical models show potential to demonstrate complex anatomical relationships; however, the literature is inconsistent as to whether they are effective in improving the anatomy performance, particularly for students with low spatial visualization ability (Vz). This study investigated the educational effectiveness of a 3D stereoscopic model of the pelvis, and the relationship between learning with 3D models and Vz. It was hypothesized that participants learning with a 3D pelvis model would outperform participants learning with a two‐dimensional (2D) visualization or cadaveric specimen on a spatial anatomy test, particularly when comparing those with low Vz. Participants ( n = 64) were stratified into three experimental groups, who each attended a learning session with either a 3D stereoscopic model ( n = 21), 2D visualization ( n = 21), or cadaveric specimen ( n = 22) of the pelvis. Medical and pre‐medical student participants completed a multiple‐choice pre‐test and post‐test during their respective learning session, and a long‐term retention (LTR) test 2 months later. Results showed no difference in anatomy test improvement or LTR performance between the experimental groups. A simple linear regression analysis showed that within the 3D group, participants with high Vz tended to retain more than those with low Vz on the LTR test ( R 2 = 0.31, P = 0.01). The low Vz participants may be cognitively overloaded by the complex spatial cues from the 3D stereoscopic model. Results of this study should inform resource selection and curriculum design for health professional students, with attention to the impact of Vz on learning.
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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 | 0.000 |
| 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 it