Approches et paradigmes pour la recherche sur les usages éducatifs des technologies: Enjeux et perspectives
Bibliographic record
Abstract
Les lignes qui suivent présentent une réflexion commencée à l’EDUsummIT de 2019 à Québec, notamment dans un groupe de travail sur les paradigmes de recherche souhaitables dans le domaine de l’étude des usages éducatifs des technologies de l’information et de la communication. Il déconstruit la notion de passage à l’échelle des innovations et interroge la tension entre différents paradigmes de recherche, critique les points de vue peu problématisés de certains décideurs qui promeuvent un type particulier de recherche se concentrant uniquement sur le passage à l’échelle uniquement en termes de résultats. Finalement, il argumente pour l’intérêt d’approches participatives plurielles associant des collectifs hybrides durables.
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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 | 0.076 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.010 | 0.041 |
| Scholarly communication | 0.028 | 0.025 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".