Development of the Competency Based Fieldwork Evaluation (CBFE)
Bibliographic record
Abstract
Abstract Recent changes in health care have contributed to an increase in community care and a consequent increase in community fieldwork sites in professional practice education. Evaluations of student performance designed before this transition are limited in their applicability across diverse settings. This article describes the development of a student performance evaluation, the Competency Based Fieldwork Evaluation (CBFE), based on a set of core competencies. Specifically, the CBFE was created to be used across a variety of rehabilitation professions: (a) to evaluate student performance in a variety of fieldwork settings, (b) to provide a cumulative record of student competency acquisition, and (c) to ensure competency for entry to practice. Focus group discussions and review of evaluations across disciplines led to the compilation of seven competencies common to all rehabilitation professions: (1) practice knowledge, (2) clinical reasoning, (3) facilitating change, (4) professional interactions, (5) communication, (6) professional development, and (7) performance management. A pilot version of the CBFE, using a visual analogue scale (VAS) for each competency, was field tested. Content analysis supported the seven competencies. However, concerns regarding the use of a VAS led to revision to a numeric rating scale with descriptors reflecting the stages of professional development. Evidence to date supports the use of the CBFE as a measure of developing clinical skills across diverse settings. However, most data have come from occupational therapy students. Future research is needed to evaluate the numeric rating scale, the reliability of the CBFE, and to evaluate the applicability of the CBFE across rehabilitation professions. Copyright © 2001 Whurr Publishers Ltd.
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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 | 0.083 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".