Le développement de l’échelle POSITIVES : satisfaction des étudiants en situation de handicap concernant les technologies de l’information et de la communication
Bibliographic record
Abstract
L’échelle POSITIVES ( Postsecondary Information Technology Initiative Scale ) porte sur les réponses de 141 étudiants francophones canadiens de niveau postsecondaire en situation de handicap concernant la satisfaction de leurs besoins reliés aux technologies de l’information et de la communication (TIC). Cet article a pour objectif de présenter des données sur les propriétés psychométriques de l’échelle et d’en proposer des utilisations futures. Sa fidélité et sa validité sont excellentes. Les résultats indiquent qu’en général l’accessibilité des sites Web et services en ligne des établissements, les heures d’accès à ces technologies et les formats alternatifs des matériels de cours sont adéquats. Par contre, la formation hors campus à ce sujet et la disponibilité des ordinateurs adaptés dans les établissements sont problématiques.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".