Rethinking the OSCE as a Tool for National Competency Evaluation
Bibliographic record
Abstract
The relatively recent curriculum change to Problem‐Based Learning/Case‐Based Education has stimulated the development of new evaluation tools for student assessment. The Objective Structured Clinical Examination (OSCE) has become a popular method for such assessment. The National Dental Examining Board of Canada (NDEB) began using an OSCE format as part of the national certification testing process for licensure of beginning dentists in Canada in 1996. The OSCE has been well received by provincial licensing authorities, dental schools and students. ‘Hands on’ clinical competency is trusted to the dental programs and verified through NDEB participation in the Accreditation process. The desire to refine the OCSE has resulted in the development of a new format. Previously OSCE stations consisted of case‐based materials and related multiple‐choice questions. The new format has case‐based material with an extended match presentation. Candidates ‘select one or more correct answers’ from a group of up to15 options. The blueprint is referenced to the national competencies for beginning practitioners in Canada. This new format will be available to students on the NDEB website for information and study purposes. Question stems and options will remain constant. Case histories and case materials will change each year. This new OSCE will be easier to administer and be less expensive in terms of test development. Reliability and validity is enhanced by involving content experts from all faculties in test development, by having the OSCE verified by general practitioners and by making the format available to candidates. The new OSCE will be pilot tested in September 2004. Examples will be provided for information and discussion.
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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 | 0.347 | 0.416 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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.
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".