Anatomy Students: The Difference between their Opinions and their Practice in Studying Anatomy
Bibliographic record
Abstract
Postsecondary institutions are choosing to use digital resources to teach the anatomical sciences, however, studies remain divided about whether these digital resources benefit students over traditional methods such as cadaveric dissection and textbooks/atlases. Recent trends in a systematic human anatomy course at the University of Western Ontario show more students registering in the online section of the course than the traditional face to face (F2F) section. As more students register for online courses, it is important to understand which resources traditional F2F students rely upon to ensure that they do not become disadvantaged should a future anatomy course change to completely online. Students in this systematic human anatomy course (n=127) were surveyed about the usefulness of several anatomy resources, including cadaveric dissection, textbooks/atlases and e‐learning tools, as well as which resources they used while studying. Students were also asked about their preference for digital and printed resources as well as the perceived value of lectures and laboratories. In this undergraduate anatomy course, F2F students attend a weekly 1‐hour cadaveric laboratory where they viewed and manipulated prosections as they interacted with teaching assistants. We hypothesized that F2F students would favor traditional study methods such as printed materials and dissection over the use of digital resources. Furthermore, because of the hand‐on experience of the prosection laboratory, we hypothesized students would value the lab experience over the anatomy lectures. Results showed that students' opinions of resource usefulness did not reflect the resources they chose to study with. When asked about the usefulness of dissection, textbook/atlases, and e‐learning tools students reported all resources as equally useful. However, despite their positive perceptions, they used lecture slides (92%) significantly more than the PowerPoint lab slides (66%), textbooks/atlases (62%), and e‐learning tools (29%; p<0.01). The overwhelming preference for lecture slides may be due to the professor's narrative that accompanies the slides. Student experience suggests that theory assessments are most often based on the material delivered in the slides. When students were surveyed about using traditional printed or digital resources, results showed that students do not follow a consistent style. Chi Square analysis indicated that printed textbooks and atlases were used significantly more often by students than electronic versions of these resources (p<0.01). Conversely, digital PowerPoint lecture and lab slides were used significantly more than their hardcopy counterparts (p<0.01). These results suggest that students prefer to use the resources supplied or suggested to them by their educators. Furthermore, students valued lectures significantly more than laboratories (p<0.001), possible because they perceived that the simple identification style of the laboratory assessment would not reflect the higher order material taught in the lab. Our results suggest that F2F students are more likely to depend on lectures and abstain from using novel methods such as e‐learning tools and thus may be disadvantaged if this course is taught in a fully online fashion using e‐learning tools.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".