Analyse statistique des profils et de l’activité des participants d’un MOOC
Bibliographic record
Abstract
L'acronyme MOOC (Massive Online Open Course) est utilisé pour désigner les plateformes d'enseignement en ligne qui proposent des cours ouverts et qui peuvent s'adresser à des centaines, des milliers, voire des dizaines de milliers d'étudiants simultanément.Le but du présent article n'est pas de proposer une analyse du phénomène MOOC dans sa généralité, mais d'offrir une vision originale d'un MOOC, au travers de ses étudiants, de leur profil et de leur activité lors du cours.Pour ce faire, nous analysons les données collectées lors d'un des premiers cours lancés sur la plateforme française FUN, le cours « Fondamentaux en statistique ».Nous y décrivons la communauté des étudiants, leur profil socioéconomique, leurs motivations, leur activité sur le forum du cours.Nous étudierons comment les échanges sur le forum se structurent lors du cours.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".