E-Learning Quality Standards for Consumer Protection and Consumer Confidence: A Canadian Case Study in E-Learning Quality Assurance.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emerging concerns about quality of e-learning products and services animated a project in Canada to create quality standards that derived primarily from the needs of consumer, that could be used to guide the development and choice of e-learning at all levels of education and training, and that could be implemented in a simple manner. A set of quality standards were created to reflect best practices in learning technologies, distance learning, and student-centred learning. The standards, first labeled the Canadian Recommended E-Learning Guidelines, are now available in the Creative Commons as the Open eQuality Learning Standards. To implement the standards, two tools were created: a Consumer’s Guide to E-learning and a certification mark — the eQcheck quality mark — to indicate that e-learning courses, modules, and programs, and elements of them, meet those quality standards. The purpose is to provide consumer confidence in the elearning enterprise and consumer protection for the investments made by individuals, agencies, and entire governments. This approach, a Canadian case study in e-learning quality assurance, differs substantially from other e-learning quality initiatives, making a unique contribution to the e-learning quality assurance dialogue.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it