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Are Clerks Ready For Clerkship? Third Year Medical Students' Anatomical Science Knowledge vs. Clerkship Director Expectations

2018· article· en· W3173827806 on OpenAlexaffabout
Madeleine E. Norris, Kem A. Rogers, Charys M. Martin

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern University
Fundersnot available
KeywordsCurriculumMedical educationTest (biology)Medical schoolUndergraduate educationPsychologyMedicineUrologyRadiologyInternal medicinePedagogyBiology

Abstract

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Introduction Competency‐based medical education (CBME) has been mandated across Canada for residency programs, encouraging undergraduate medical education (UME) programs to adopt this model. Schulich is undergoing a curriculum renewal to implement CBME at the UME level; however, there is limited research on how to effectively integrate anatomical sciences into a CBME model. Further, the anatomical concepts taught, and pedagogical methods employed, varies widely across curricula. Currently at Schulich, the anatomical science knowledge that clerkship directors expect students to learn prior to clerkship, and how much anatomical science knowledge current students retain, is unclear. By determining the effectiveness of the current anatomical science curriculum, we can inform the design and delivery of anatomical sciences into the CBME model. Thus, the specific aims of this research are to: (1) determine which anatomical science concepts are necessary for clerkship, and (2) assess third‐year medical students' anatomical science knowledge retention prior to and at the completion of each clerkship rotation. It was hypothesized that (1) paediatrics clerkship directors would deem embryology more important, compared to clerkship directors for surgery, where gross anatomy would take precedence. Furthermore, (2) third‐year medical students would score low on the pre‐test, due to limited knowledge retention after completing pre‐clerkship, and score higher on the post‐test as a result of the learning that takes place during clerkship. Methods (1) Questionnaires were created and used to guide interviews with all UME clerkship directors to determine which anatomical science concepts are thought to be necessary for each clerkship rotation. Interviews were transcribed and coded according to anatomical science themes mentioned. (2) Using information from Aim 1, a multiple choice assessment was created for each rotation to measure students' anatomical knowledge prior to and at the completion of each clerkship rotation. Results Embryology was the most prevalent anatomical science theme, and histology was the least. When analyzing each rotation, embryology was most prevalent for surgery, paeds, and family med., while imaging, neuroanatomy, and gross anatomy took precedence for internal med., psychiatry, and OB/GYN, respectively. Preliminary assessment results for four rotations reveal that students entering OB/GYN, family med., and psychiatry rotations achieved an average passing grade (>60%) on the pre‐test, while students entering paeds did not. When comparing the pre‐ and post‐tests, there was a significant improvement for students completing the paeds rotation (p=.009, d=.95). Conclusion Embryology being the most prevalent theme in surgery, paeds, and family med., and second most frequent in OB/GYN, suggests that these specialties rely on knowledge of normal development. Preliminary assessment data indicated that even though students entering paeds did not achieve an average passing grade on the pre‐test, which could be due to the challenging embryological concepts, this group of students displayed significant improvement on the post‐test, suggesting that learning of embryological concepts occurs during the rotation. The concepts deemed necessary by clerkship directors will be mapped to where and how they are taught within the current curriculum, which will elucidate curricular strengths and weaknesses, and help guide the curriculum reform. Support or Funding Information Ontario Graduate Scholarship This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.050
GPT teacher head0.409
Teacher spread0.359 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2018
Admission routes2
Has abstractyes

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