A Mismatch From the Start? A Comparison of CANeLearn Design Principles for Online Learning with NSQOL and QM Standards
Bibliographic record
Abstract
In February 2021 the Canadian eLearning Network (CANeLearn) began engaging educators across Canada in facilitated conversations about teaching in online learning environments.While the process began in British Columbia (BC) (Crichton & Kinsel, 2021), the confirmation of the derived "design principles" were shared with participants across Canada in both anglophone and francophone online programs.The resulting modified design principles from the national validation process were published by CANeLearn in February 2022 (Crichton & Childs, 2022).However, the concept of using design principles to describe the practice of K-12 online learning is relatively new so CANeLearn invited K-12 researchers to examine a variety of standards related to K-12 online learning in an effort to situate them within the CANeLearn design principles.After the analysis was completed it was found that, at best, the design principles set a context or process while the NSQOL and QM standards described an observable outcome or action.As such, it was suggested that standards could offer examples that could be used to support the Design Principles for K-12 Online Learning.Additional research needs to be done to explore that notion as well as the relationship of CANeLearn's Design Principles for K-12 Online Learning to other prevalent researched models of online learning.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".