Maitrise d’outils technologiques : son influence sur la compétence TIC des enseignants et les usages pédagogiques | Mastery of Digital Tools: The Influence on Information and Communication Technologies Competency and Pedagogical Use
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
L’utilisation des technologies de l’information et de la communication (TIC) en contexte éducatif est un enjeu important pour les enseignants du préscolaire-primaire et du secondaire au Québec. Dans cette recherche, nous avons examiné dans quelle mesure la maitrise d’outils numériques peut prédire des usages pédagogiques déclarés. Nous avons également étudié la relation prédictive entre le niveau déclaré de maitrise des outils numériques par les enseignants et leur compétence professionnelle à intégrer les TIC. Les régressions montrent que la maitrise du tableau numérique interactif prédit positivement des usages pédagogiques du numérique et une bonne maitrise de la compétence à intégrer les TIC.The use of information and communication technologies (ICT) is an important issue for many preschool, elementary, and secondary school teachers in Québec. In this study, we examined to what extent the mastery of digital tools can predict reported pedagogical usage. Also, we used the level of mastery of digital tools by teachers as a variable to assess the predictive impact of the components of professional competence on the integration of ICT. The results of the regression indicate that the mastery of the interactive whiteboard positively predicts the pedagogical use of ICTs as well as a good mastery of the integration of ICTs.
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.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it