Évaluation de la formation en transfert de connaissances à l’Institut Pasteur de Madagascar
Bibliographic record
Abstract
Cette étude évaluative porte sur la mise en œuvre et les effets perçus d’une formation en présence sur le transfert de connaissances, qui s’appuie sur deux cours en ligne ouverts et massifs (massive open online course – MOOC). La formation ciblait des membres du personnel ainsi que des partenaires de l’Institut Pasteur de Madagascar. L’étude a suivi le modèle de Kirkpatrick pour évaluer les effets perçus de la formation et le cadre TIPEC (Technology, Individual, Pedagogy and Enabling Conditions) pour identifier les facilitateurs et les obstacles de sa mise en œuvre. La collecte des données a suivi un devis mixte convergent. Trente-deux personnes (32) ont répondu au questionnaire de préformation, dont 18 personnes au questionnaire postformation et 24 à des entretiens semi-dirigés cinq mois après la fin de la formation. La plupart des personnes ont indiqué que la formation à l’aide des MOOC et d’un accompagnement en présence a répondu à leurs besoins, bien que son intensité et son niveau élevé de difficulté aient été soulignés par certains. Le volet pratique de la formation ainsi que la présence d’une formatrice ou d’un formateur ont été jugés essentiels à l’apprentissage. Les résultats suggèrent que le format pédagogique adopté pourrait constituer un outil pertinent et accessible pour la formation continue des professionnels. Mots clés : Transfert des connaissances, renforcement des capacités, MOOC, évaluation, Madagascar Evaluation of Knowledge Translation Training at the Institut Pasteur de Madagascar Abstract: This evaluative study focuses on the implementation and perceived effects of an in-person training program on knowledge translation, which is based on two massive open online courses (MOOCs). The training targeted staff members as well as partners of the Institut Pasteur de Madagascar. The study followed the Kirkpatrick model to evaluate the perceived effects of the training and the TIPEC framework (Technology, Individual, Pedagogy, and Enabling Conditions) to identify facilitators and barriers to its implementation. Data collection was guided by a convergent mixed-methods design. Thirty-two people completed the pre-training questionnaire, of these, 18 responded to the post-training questionnaire and 24 took part in semi-structured interviews five months after the training ended. Most participants indicated that the training, combining MOOCs with in-person support, met their needs, although some highlighted its intensity and high level of difficulty. The practical component of the training and the presence of a trainer were deemed essential to learning. The results suggest that the adopted pedagogical format may represent a relevant and accessible tool for the continuing education of professionals. Keywords: knowledge translation, capacity building, MOOC, evaluation, Madagascar
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 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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".