“We Learn by Doing”: Teaching and Learning Knowledge Translation Skills at the Graduate Level
Bibliographic record
Abstract
Knowledge Translation (KT) is increasingly a requirement for scholars and non-academics working in applied settings. However, few programs provide explicit training in KT. In this article we systematically explore our experiences as a multi-disciplinary group of course facilitators and students in a newly redeveloped graduate course in Evidence Based Practice and Knowledge Translation. The course was designed to emphasize hands-on learning, collaboration and community engagement. We reflect on the challenges we faced and the skills, knowledge and opportunities that students gained as they developed and implemented community-based KT strategies relating to refugee resettlement, young carers, and consumer attitudes, behaviour and values around food purchasing decisions. We conclude by providing recommendations for instructors and institutions for implementing learning experiences in KT that are designed for real-world impact. L’application des connaissances (AC) est devenue une exigence de plus en plus fréquente pour les chercheurs et les personnes qui travaillent dans les milieux non universitaires. Toutefois, peu de programmes offrent une formation explicite en AC. Dans cet article, nous explorons systématiquement nos expériences en tant que groupe pluridisciplinaire formé de responsables de cours et d’étudiants dans un cours de cycle supérieur nouvellement remanié portant sur la pratique fondée sur les données probantes et l’application des connaissances. Le cours a été conçu pour mettre en valeur l’apprentissage pratique, la collaboration et l’engagement communautaire. Nous réfléchissons aux défis auxquels nous avons été confrontés ainsi qu’aux compétences, aux connaissances et aux opportunités que les étudiants ont acquis en développant et mettant en pratique des stratégies d’AC en milieu communautaire sur les thèmes de la réinstallation des réfugiés, des jeunes aidants et des attitudes, comportements et valeurs des consommateurs en matière d’achat de produits alimentaires. En conclusion, nous présentons des recommandations à l’intention des enseignants et des établissements pour la mise en pratique d’expériences en AC qui soient conçues pour avoir un effet dans le monde réel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.035 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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".