Principles-Focused Evaluation: A Promising Practice in the Evaluation of Continuing Professional Development
Bibliographic record
Abstract
ABSTRACT: Outcome-based evaluations still dominate in continuing professional development (CPD) despite the availability of evaluation approaches that address program processes and contexts. Our continued reliance on outcomes-based evaluation fails to respect the importance of complexity and the human element of program planning and implementation. Therefore, it is time that the field of CPD embrace complementary approaches to program evaluation that consider the complexity and maturity of programs and their contexts, while providing credible and relevant information to inform strategic decisions regarding the future of a program. Principles-focused evaluation provides a complement to traditional evaluation approaches through the articulation of a program's values that can be actioned. These "actionable values," known as principles, become the focus of the evaluation for the purposes of program decision-making. This paper describes how one CPD program, designed as a response to growing opioid-related harms, adopted a principles-focused evaluation to inform ongoing iteration of the program. The process used to design the principles, how the principles are informing the transportability of the program, and implications for CPD evaluation are discussed.
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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 | 0.525 | 0.429 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".