Canadian Physiotherapy Assessment of Clinical Performance: Face and Content Validity
Bibliographic record
Abstract
PURPOSE: To investigate face and content validity of a draft measure to be used across Canada to assess physiotherapy students' performance in clinical education, through broad consultation with physiotherapy clinical instructors (CIs) across Canada. METHODS: An online survey was used to collect input on the draft measure. In addition to demographics, the questionnaire included questions on the preferred rating scale, the items within the measure that should have their own rating scale, and general impressions. RESULTS: Among the 259 CIs who completed the survey, a discrete rating scale with six anchors and 10 boxes or a continuous-line rating scale with six anchors was preferred. Respondents favoured using one rating scale for each key competency in the Expert role but considered a single rating scale sufficient for assessing the Scholarly Practitioner role. CIs agreed that the proposed measure would allow them to assess a student who was performing poorly or very well. The name Canadian Physiotherapy Assessment of Clinical Performance (ACP) received the most votes in the questionnaire. CONCLUSIONS: CIs' collective preferences on the design, organization, and naming of the measure they will use in evaluating students are reflected in the second draft of the ACP.
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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 | 0.014 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".