The Embryology Educator Experience: A Comprehensive Survey of Faculty and the Generation of a Phenomenology of Embryology Education
Bibliographic record
Abstract
There has been a noted decrease in the time and resources devoted to embryology in medical education in the past fifty years. With more changes assured, it is necessary to investigate current patterns and establish what is truly needed for the education of future physicians. To address these concerns, the researcher distributed an online mixed methods survey to current anatomy and embryology faculty and conducted follow‐up interviews with volunteers from that cohort. Thirteen months of data collection yielded 62 participants. Of these individuals, 69% instruct students at allopathic medical schools, 13% at osteopathic medical schools, and the remaining 18% of participants teach at dentistry, other clinical or professional schools, or undergraduate four‐year institutions. The 55 represented schools are distributed widely across North America. In the United States, 20 schools were from the South, 16 from the Midwest, 9 from the Northeast, and 7 from the West. Three schools were from Canada. The survey included questions about curriculum format, teaching experience, resources, and perceptions of embryological content. While 62% of participants reported an integrated curriculum, 32% had separate courses, and 6% had another alternative curricular format. Most participants primarily taught gross anatomy and embryology, and 40% of these individuals had more than 20 years of teaching experience. The researcher used a grounded theory methodology and NVivo qualitative data analysis software to analyze the open‐ended questions regarding what faculty find most interesting or confusing about embryology, and solicitation of suggestions for the improvement of embryology education. Major themes for all three categories included visualization and resources, curricular placement, clinical relevance, and the continual addition of new embryological content via molecular research. A combined grounded theory and phenomenological approach was used to analyze the 13 follow‐up interviews. This generated a “lived experience” narrative of the phenomenon of teaching embryological content to medical students in the modern world, which led to a better understanding of the needs and challenges that face this subject matter and those who teach it. In this fluid time of medical education reform and integration, the experiences and perceptions of faculty in anatomy and embryology are invaluable to assessing the curriculum and formulating evidence‐based curriculum guidelines for the future.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".