Does an Online Clinical Educator Preparation and Support Program Change Practice?
Bibliographic record
Abstract
Preparation of clinicians to act as student placement supervisors is important to ensure quality student placements for the development of the skills needed for competent performance in the workplace. Clinical educator preparation programs are offered in many formats, but these programs are rarely evaluated for impact on practice. In this article, we describe the results of the evaluation of an online clinical educator preparation and support (CEPS) program. Thirty allied health professionals, across a range of professions, responded to a survey regarding their experience of the program, usage patterns and their application of learning to practice. As a result of participation in the program, there was a significant increase in confidence levels in a number of topic areas covered in the program, and a quarter of respondents had changed their student supervision practices as a result of participation. Due to a low response rate at the three month follow-up survey, planned interviews to explore the impact of change in practice on the student placement experience could not be completed. While the study was not able to measure the impact of the CEPS program on placement quality, it did show that the CEPS program is able to significantly increase supervisor confidence in a number of areas, and is able to effect change in practice.
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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 | 0.016 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".