Unmasking the Structure of Gross Anatomy Laboratory Sessions During Covid‐19
Bibliographic record
Abstract
INTRODUCTION/OBJECTIVE Covid‐19 created immediate challenges to anatomy education. The traditional format of gross laboratory sessions experienced a direct impact and few reports documented curricular delivery changes specific to laboratory format. The purpose of this study was to assess the adaptations incorporated in gross anatomy laboratories by anatomists, during May‐August 2020, in response to Covid‐19. MATERIALS/METHODS Data were collected through the IRB‐approved Virtual Anatomy During Covid‐19 survey that consisted of 20 questions, including open‐ended prompts asking participants to describe the structure of a “typical” laboratory session during Covid‐19. Responses were solicited from professional anatomy associations during June 2020. Open‐ended responses describing anatomy laboratory teaching methods used during Covid‐19 were coded. Descriptive codes were applied to the data according to published methods to summarize verbatim responses. Responses were tabulated and converted to frequencies and percentages. Chi square test assessed differences among the responses when applicable. Alpha<5%. RESULTS Descriptions of gross anatomy lab teaching during Covid‐19 were coded into four categories : (1) delivery format, (2) format of laboratory practice, (3) type of anatomy digital resources used, and (4) format of student teaching groups. In the first category, synchronous (46.7%), asynchronous (15.6%), and/or a combination of the two (18.8%) were the most frequent laboratory delivery formats (P<0.001). In the second category, student‐led dissection (17.2%), prosection (10.9%), and/or utilization of commercial and/or in‐house anatomical resources (26.2%) were the most frequent laboratory practices (P<0.001). Within this category, a subcategory was discovered in which physical distancing and personal protective equipment practices were reported (15.6%). Concerning the third category, anatomy digital resources (26.2%) were used for asynchronous laboratory preparation and laboratory sessions. In the final category, student small groups (29.7%) were used in remote sessions where “breakout rooms” permitted students to meet with peers and/or faculty. Large groups (9.4%) were used for faculty to review and present the assigned laboratory topic. CONCLUSION Anatomists largely taught through a remote, synchronous delivery format that relied on cadaveric specimens and digital anatomy resources, as well as small group learning. SIGNIFICANCE/IMPLICATION: This study shows that anatomists were able to adapt the gross anatomy laboratory sessions to synchronous, virtual mediums; however, the impact of these changes to the learner during this unconventional time remains to be determined.
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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 | 0.017 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".