Veterinary e-CPD: A New Model for Providing Online Continuing Professional Development for the Veterinary Profession
Bibliographic record
Abstract
Continuing professional development (CPD) is widely recognized as an important element in effective lifelong learning for veterinary surgeons. Traditional methods of CPD do not suit all learners, as issues such as location, time, cost, and structure sometimes prevent individuals from completing the required number of CPD study hours per year. The rapid development of the Internet, and with it the increasing scope and sophistication of e-learning, provides new opportunities to address some of these constraints on the provision of CPD. This article describes one way in which e-learning has been deployed effectively to support veterinary surgeons in practice. Since 2003, a series of six-week e-CPD courses has been offered by the Royal Veterinary College (RVC) in an online format, with no face-to-face teaching component. Participants enrolled in courses from May 2006 to January 2007 were found to come from 23 different countries. Analysis of feedback forms indicates a general satisfaction with this new way of studying, with a significant majority of participants stating that they would wish to use this approach again in future. The feedback indicates that e-learning can offer an effective alternative to traditional face-to-face courses and that its popularity is likely to grow in future as veterinarians become increasing familiar with and confident about working online.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".