COORDINATING THE INSTRUCTION OF FOUR ONLINE COURSES
Bibliographic record
Abstract
The University of British Columbia Vantage College offers a pathway for academically qualified international students who do not yet meet the English language admission requirements fordirect entry into UBC. In the summer of 2020, during the COVID-19 pandemic, we taught four courses to a cohort of 64 students scattered across the globe. The courses were taught online and asynchronously, raising coordination challenges in terms of class schedule and delivery, assessment, and student support. To address those challenges, we developed a highly structured weekly schedule, specifying lecture and assessment days, as well as regular, synchronous office hours. We met weekly to keep each other updated about the progress of students. Students falling behind in multiple courses were reported in an “early alert” system: a university-specific resource through which students are contacted by health and wellness staff. A midterm survey was conducted and the feedback was generally positive. Final results in the courses were varied, with some comparable
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.017 |
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".