Evolution of the Instructional Design in a Series of Online Workshops | L’évolution d’un design pédagogique dans le développement d’ateliers en ligne
Bibliographic record
Abstract
This case recounts the story of the design and production of a series of online workshops for French-speaking healthcare professionals in Canada. The project spans a couple of years and, despite encountering some challenges, succeeds in large part because of its strong foundation: the instructional design. This case study features an instructional designer from a central Canadian university and three SMEs. The main design issues highlighted are the target population’s limited availability for continuing education, the SME’s lack of knowledge of the instructional design process, the magnitude of this project with its national scope but limited time frame and human resources, as well as personnel changes among the SMEs and the instructional design team. This case outlines how the project team deals with these challenges to produce a series of online workshops that provide high quality training in French to healthcare professionals across Canada.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".