Digging Up: A Five-Year Journey to Instructional-Design Stability in a Postsecondary Distance Education Unit
Bibliographic record
Abstract
This report of practice describes a five-year process to establish and implement quality standards for a substantial portfolio of distancedelivered courses at the Centre for Continuing and Distance Education, University of Saskatchewan. The report describes an analysis of the issues and the solutions found that led to our current curriculum design standards and procedures, the implementation of learning technologies, and the identification of issues and solutions regarding copyright law. Lastly, the future prospects of these distance-delivered postsecondary courses are considered. Focusing on the issues and solutions for each category of challenges, this report describes the five-year journey of a small instructional-design team that faced roadblocks and barriers common to many postsecondary continuing and distance education units.
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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 | 0.030 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".