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Record W2090747809 · doi:10.1186/1472-6920-10-93

Musculoskeletal education: a curriculum evaluation at one university

2010· article· en· W2090747809 on OpenAlexaffabout
Marcia Clark, Carol Hutchison, Jocelyn Lockyer

Bibliographic record

VenueBMC Medical Education · 2010
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsCurriculumStrengths and weaknessesMedical educationBlueprintCourse evaluationMedicinePsychologyHigher educationPedagogyEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: The increasing burden of illness related to musculoskeletal diseases makes it essential that attention be paid to musculoskeletal education in medical schools. This case study examines the undergraduate musculoskeletal curriculum at one medical school. METHODS: A case study research methodology used quantitative and qualitative approaches to systematically examine the undergraduate musculoskeletal course at the University of Calgary (Alberta, Canada) Faculty of Medicine. The aim of the study was to understand the strengths and weaknesses of the curriculum guided by four questions: (1) Was the course structured according to standard principles for curriculum design as described in the Kern framework? (2) How did students and faculty perceive the course? (3) Was the assessment of the students valid and reliable? (4) Were the course evaluations completed by student and faculty valid and reliable? RESULTS: The analysis showed that the structure of the musculoskeletal course mapped to many components of Kern's framework in course design. The course had a high level of commitment by teachers, included a valid and reliable final examination, and valid evaluation questionnaires that provided relevant information to assess curriculum function. The curricular review identified several weaknesses in the course: the apparent absence of a formalized needs assessment, course objectives that were not specific or measurable, poor development of clinical presentations, small group sessions that exceeded normal 'small group' sizes, and poor alignment between the course objectives, examination blueprint and the examination. Both students and faculty members perceived the same strengths and weaknesses in the curriculum. Course evaluation data provided information that was consistent with the findings from the interviews with the key stakeholders. CONCLUSIONS: The case study approach using the Kern framework and selected questions provided a robust way to assess a curriculum, identify its strengths and weaknesses and guide improvements.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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.

Opus teacher head0.010
GPT teacher head0.322
Teacher spread0.312 · 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 teacher head, not a consensus.

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

Citations18
Published2010
Admission routes2
Has abstractyes

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