MétaCan
Menu
Back to cohort
Record W4411501401 · doi:10.1002/ase.70072

A scoping review of teaching approaches and learning objectives for anatomical variation in gross anatomy courses across degree programs

2025· review· en· W4411501401 on OpenAlexaff
Kayla Vieno‐Corbett, Nicole Campbell, Angela Pecyna, Kem A. Rogers

Bibliographic record

VenueAnatomical Sciences Education · 2025
Typereview
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsWestern University
Fundersnot available
KeywordsVariation (astronomy)Gross anatomyMedical educationPsychologyDiversity (politics)MedicineAnatomy

Abstract

fetched live from OpenAlex

Gross anatomy is often taught and assessed based on a "standard" view of the human body, limiting students' exposure to normal variation, creating a potential curricular gap in the training of future anatomists and health care professionals. This scoping review explores learning objectives and teaching approaches associated with anatomical variation in undergraduate, graduate, and professional courses. Six primary databases and gray literature sources were searched. Records that described either implicit or explicit approaches for teaching anatomical variation in gross anatomy courses at the undergraduate, graduate, or professional level were included. Source selection, data extraction, and analysis followed the JBI Manual for Evidence Synthesis. Human donor dissection was the most common approach for implicitly teaching anatomical variation (35.7%, 56/157). Only a few records (25.5%, 40/157) reported examples of explicit teaching approaches, such as student recordings of variation, exposure to multiple donors, and independent research. Reported learning objectives primarily involved awareness, appreciation, and knowledge of anatomical variation. Other learning objectives included the recognition of human diversity, professionalism, collaboration, knowledge through anatomical variation, and navigating anatomical variation. Objectives were mapped to Bloom's Taxonomy, showing that explicit approaches were associated with higher-order learning. This review highlights a gap in the literature regarding the explicit teaching of anatomical variation despite the benefits of explicit approaches for enabling higher-order levels of learning across multiple domains. Recognizing anatomical variation is essential for health care professionals, and this review suggests a need for intentional instructional strategies to better support students in navigating anatomical diversity in educational and clinical contexts.

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 imitation

Not 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.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.031
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.163
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0310.029
Science and technology studies0.0020.002
Scholarly communication0.0050.005
Open science0.0030.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.058
GPT teacher head0.401
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAnatomical Sciences EducationSame topicAnatomy and Medical TechnologyFrench-language works237,207