Bibliographic record
Abstract
La question de l'efficacité pédagogique des TICE (technologies d'information et de communication pour l'enseignement) est redoutable. On a envie de dire que c'est une question impossible.Comme il y a des croyants et des athées, il y a des partisans des TICE et des adversaires des TICE, mais aussi des agnostiques, qui ne se prononcent pas, soit parce qu'ils attendent qu'une preuve leur soit apportée, d'un côté ou de l'autre, soit qu'ils considèrent la question comme insoluble ou sans intérêt. Les croyants des TICE sont aujourd'hui les plus nombreux . Et face aux voix qui s'élèvent pour dire : " les TICE ne servent à rien ! ", la réaction est souvent brutale et la contre-critique sans nuance. Pour ne pas raviver inutilement de récentes querelles françaises, on se contentera d'évoquer ici certaines de celles qui se tiennent aux États-Unis et au Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.037 |
| Scholarly communication | 0.020 | 0.031 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".