Analyse statistique des profils et de l’activité des participants d’un MOOC
Bibliographic record
Abstract
L'acronyme MOOC (Massive Online Open Course) est utilis pour dsigner les plateformes d'enseignement en ligne qui proposent des cours ouverts et qui peuvent s'adresser des centaines, des milliers, voire des dizaines de milliers d'tudiants simultanment. Le but du prsent article n'est pas de proposer une analyse du phnomne MOOC dans sa gnralit, mais d'offrir une vision originale d'un MOOC, au travers de ses tudiants, de leur profil et de leur activit lors du cours. Pour ce faire, nous analysons les donnes collectes lors d'un des premiers cours lancs sur la plateforme franaise FUN, le cours Fondamentaux en statistique . Nous y dcrivons la communaut des tudiants, leur profil socioconomique, leurs motivations, leur activit sur le forum du cours. Nous tudierons comment les changes sur le forum se structurent lors du cours.
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How this classification was reachedexpand
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".