Beyond content knowledge: psychosocial attitude, behavior, and skill development in gross anatomy education
Bibliographic record
Abstract
IntroductionIncreasing evidence suggests that acquisition of a variety of different attitudes, skills, and behaviors (or ‘non‐technical content [NTC]’) are core to gross anatomy education, alongside discipline‐based knowledge. Examples of NTC include human ethics, teamwork, and professionalism. Human donors and laboratory experiences typically serve as the foundation of NTC curriculum development and assessment. With many global institutions shifting from in‐person, human dissections to virtual laboratories, in response to the COVID‐19 pandemic, we sought to explore anatomists’ views on NTC within this novel virtual environment. MethodsEngaging mixed methods study design, and a pragmatist theoretical lens ‐ a voluntary survey (IU IRB# 2006285000) was developed and distributed internationally from July to November 2020. Additional to demographic information (including information about courses taught), questions about anatomists’ views of the importance, extent and types of NTC relevant to student learning were posed. The context included anatomists’ perceptions of these NTC both prior to and during their pandemic teaching experiences. Data were analyzed using SPSS v. 27. Differences between NTC and their assessment prior to and during the pandemic were compared using paired samples t‐test and Wilcoxon signed rank test. Free responses were analyzed using thematic analysis.Results Survey responses (n=82) represented all continents except Antarctica. Pre‐COVID‐19, respondents delivered 12% of their content online which increased to 66% online content delivery during the pandemic. Regarding the NTC, respondents expected students to acquire, only 37% is formally assessed. Overall, there was a significant decrease in the NTC assessment during the pandemic (p=0.001). Greater than 35% of respondents reported assessing the following content pre‐COVID‐19: respect for donors, teamwork, communication, clinical reasoning, and professionalism. During COVID‐19, almost all of these categories significantly decreased in the number of respondents who planned to assess these (p≤ 0.001). Fifty‐five respondents (67%) provided free responses highlighting concerns about acquisition of empathy, respect for donors, and teamwork due to reduced or eliminated dissection. ConclusionAnatomy educators report incorporating strategies into their courses to foster student development of NTC. Acquisition of these important skills remains largely a part of the hidden curriculum based on percentage of respondents assessing them. This percentage further decreased in the virtual environment. Given the availability of formative assessment types we encourage more robust and explicit incorporation into the formal curriculum.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".