An absolutely riveting online course: Nine principles for excellence in web-based teaching
Bibliographic record
Abstract
This article explores excellence in web-based teaching. Drawing on the views of experts in the field and the perspective of their own years of experience, the authors compiled a list of 9 principles to provide direction in the search for online excellence. The principles include: the online world is a medium unto itself; sense of community and social presence are essential to online excellence; in the online world, content is a verb; great online courses are defined by teaching, not technology. The list is not intended to be an exclusive set of principles or a comprehensive guide to online teaching. Rather it is a collection of important ideas and suggestions for teaching excellence in the online world. Un cours en ligne absolument captivant : Neuf principes pour l’excellence en enseignement sur le Web Résumé : Cet article explore l’excellence en enseignement sur le Web. En s’inspirant des point de vues des experts du domaine ainsi que de la perspective de leurs propres années d’expérience, les auteurs ont compilé une liste de neuf principes offrant une piste dans la quête de l’excellence en ligne. Les principes incluent : le monde en ligne est un univers en soit; un sens de communauté et de présence sociale sont essentiels à l’excellence en ligne; dans l’univers en ligne, le contenue est le verbe; les excellents cours en ligne sont définis par la pédagogie et non pas par la technologie. L’intention de la liste n’est pas de représenter un ensemble exclusif de principes, ou un guide complet de l’enseignement en ligne. Celle-ci se veut plutôt une collection d’idées et de suggestions pour l’excellence en enseignement en ligne.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.006 |
| 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".