Examining peer learning as a strategy for advancing uptake of evidence-based practices: a scoping review
Bibliographic record
Abstract
Background: Continued evolution of knowledge-to-action (KTA) theories requires increased attention to dynamics of power and ways to integrate multiple forms of knowledge. Peer learning – a process through which knowledge users interact with other learners – is a valuable but largely unexamined strategy for integrating practice-based knowledge in the KTA process. Aims and objectives: This study undertakes a scoping review to examine how peer-learning strategies have been used to advance knowledge users’ capacity for implementing evidence-based practices. Methods: A search of ten online databases and a manual search of five journals was conducted to identify studies published between 2001 and 2018. Selected publications included 26 studies conducted in Canada, the US, the UK, Australia, and the Netherlands. Studies utilised peer learning as a capacity-building strategy to advance the uptake or implementation of evidence-based practices among professionals in social services, education, or health/mental health sectors. Findings: Links between peer-learning strategies and multiple individual and/or collective capacities for implementing evidence-based practices were identified from selected studies. Individual capacities linked to peer learning include knowledge of the practice, attitudes (for example, motivation and ‘buy-in’), and practical skills. Collective capacities supported through peer learning included knowledge exchange, knowledge generation, relationship development, networking, and resource/tool sharing. Peer learning was often paired with didactic or expert-led activities. Discussion and conclusions: This scoping review identifies how peer learning has been used as a capacity-building strategy in implementation initiatives. Peer-learning activities provide a means to help integrate multiple forms of knowledge in the KTA process.
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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 | 0.012 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".