Student perceptions and effectiveness of an innovative learning tool: Anatomy Glove Learning System
Bibliographic record
Abstract
A trend in anatomical education is the development of alternative pedagogical approaches to replace or complement experiences in a cadaver laboratory; however, empirical evidence on their effectiveness is often not reported. This study aimed to evaluate the effectiveness of Anatomy Glove Learning System (AGLS), which enables students to learn the relationship between hand structure and function by drawing the structures onto a worn glove with imprinted bones. Massage therapy students (n = 73) were allocated into two groups and drew muscles onto either: (1) the glove using AGLS instructional videos (3D group); or (2) paper with palmar/dorsal views of hand bones during an instructor-guided activity (2D group). A self-confidence measure and knowledge test were completed before, immediately after, and one-week following the learning conditions. Self-confidence of hand anatomy in the 3D group gradually increased (3.2/10, 4.7/10, and 4.8/10), whereas self-confidence in the 2D group began to decline one-week later (3.2/10, 4.4/10, and 3.9/10). Knowledge of hand anatomy improved in both groups immediately after learning, (P < 0.001). Students' perceptions of AGLS were also assessed using a 10-pt Likert scale evaluation questionnaire (10 = high). Students perceived the AGLS videos (mean = 8.3 ± 2.0) and glove (mean = 8.1 ± 1.8) to be helpful in improving their understanding of hand anatomy and the majority of students preferred AGLS as a learning tool (mean = 8.6 ± 2.2). This study provides evidence demonstrating that AGLS and the traditional 2D learning approach are equally effective in promoting students' self-confidence and knowledge of hand anatomy.
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.
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 | 0.002 | 0.011 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".