Twelve tips for rapidly migrating to online learning during the COVID-19 pandemic
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
This article was migrated. The article was marked as recommended. The COVID-19 pandemic has resulted in a massive adaptation in health professions education, with a shift from in-person learning activities to a sudden heavy reliance on internet-mediated education. Some health professions schools will have already had considerable educational technology and cultural infrastructure in place, making such a shift more of a different emphasis in provision. For others, this shift will have been a considerable dislocation for both educators and learners in the provision of education. To aid educators make this shift effectively, this 12 Tips article presents a compendium of key principles and practical recommendations that apply to the modalities that make up online learning. The emphasis is on design features that can be rapidly implemented and optimised for the current pandemic. Where applicable, we have pointed out how these short-term shifts can also be beneficial for the long-term integration of educational technology into the organisations' infrastructure. The need for adaptability on the part of educators and learners is an important over-arching theme. By demonstrating these core values of the health professions school in a time of crisis, the manner in which the shift to online learning is carried out sends its own important message to novice health professionals who are in the process of developing their professional identities as learners and as clinicians.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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