2D and 3D Stereoscopic Videos Used as Pre-Anatomy Lab Tools Improve Students' Examination Performance in a Veterinary Gross Anatomy Course
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
The hypothesis for the research described in this article was that viewing an interactive two-dimensional (2D) or three-dimensional (3D) stereoscopic pre-laboratory video would improve efficiency and learning in the laboratory. A first-year DVM class was divided into 21 dissection teams of four students each. Primary variables were method of preparation (2D, 3D, or laboratory manual) and dissection region (thorax, abdomen, or pelvis). Teams were randomly assigned to a group (A, B, or C) in a crossover design experiment so that all students experienced each of the modes of preparation, but with different regions of the canine anatomy. All students were instructed to study normal course materials and the laboratory manual, the Guide, before coming to the laboratory session and to use them during the actual dissection as usual. Video groups were given a DVD with an interactive 10-12 minute video to view for the first 30 minutes of the laboratory session, while non-video groups were instructed to review the Guide. All groups were allowed 45 minutes to dissect the assigned section and find a list of assigned structures, after which all groups took a post-dissection quiz and attitudinal survey. The 2D groups performed better than the Guide groups (p=.028) on the post-dissection quiz, despite the fact that only a minority of the 2D-group students studied the Guide as instructed. There was no significant difference (p>.05) between 2D and 3D groups on the post-dissection quiz. Students preferred videos over the Guide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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 it