Regard de futurs enseignants sur l’importance des compétences TIC (Internet) pour les jeunes et la responsabilité de divers intervenants à cet égard
Bibliographic record
Abstract
Au 21e siècle, les compétences « TIC » sont importantes \npour l’intégration des individus à la société et la \ncompétitivité des nations. Plusieurs nations ont \nd’ailleurs ajusté leurs curriculums, attribuant cette \nresponsabilité à l’école. Mais qu’en pensent les futurs \nenseignants? Considèrent-ils qu’il revient à l’école \nde prendre en charge le développement de ces \ncompétences? À cet égard, nous avons demandé à 328 \nfuturs enseignants suisses, français et québécois de \nse positionner, à l’aide d’une échelle de Likert, quant \nà l’importance de 21 compétences/connaissances \nTIC et de nous préciser qui devrait, selon eux, être \nresponsable de l’encadrement du développement de chacune. \n \nIn the 21st century, « ICT » skills are important for \nthe integration of individuals into society and the \ncompetitiveness of nations. Several nations have \nadjusted their curricula, assigning this responsibility \nto the school. But what do pre-service teachers think? \nDo they believe it is for the school to support the \ndevelopment of these skills? In this regard, we asked \n328 student teachers from Switzerland, France and \nQuebec to position themself about the importance of \n21 ICT skills/knowledge using a Likert scale and tell us \nwho should, according to themselves, be responsible \nfor supervising the development of each.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".