Stratégies de prise de notes à l'aide d'une tablette électronique chez des étudiants du secondaire | Digital Tablet Note-Taking Strategies among High School Students
Bibliographic record
Abstract
Both media and digital literacies are essential for the 21st century. Consequently, several governments have integrated technologies with school curriculums. Recently, ICT integration efforts, particularly with the digital tablet, have multiplied. Several academic uses of the tablet are explored, and some raise questions. This is the case of note taking as viewed in a single Quebec high school. Which application should students use, and should it be the same one for all subjects? Is it effective? Which strategies should be promoted? These are not trivial questions where educational success is concerned. Whereas note taking using certain technological tools has already been studied, little research has focused on with the use of a digital tablet. Students who use a tablet daily were asked a series of questions related to note taking. Our analysis suggests that teachers should play an active role in the appropriation of this tool.Les littératies médiatique et numérique sont essentielles pour le 21e siècle. Plusieurs gouvernements les intègrent par conséquent aux curriculums scolaires. Actuellement, les efforts d’intégration de la tablette numérique se multiplient. Plusieurs usages scolaires sont cités et certains soulèvent des interrogations. C’est le cas de la prise de notes qui soulève des questions auprès de plusieurs enseignants d’une école secondaire québécoise. Avec quelle application? Une seule? Toujours la même? Dans toutes les matières ? Est-ce efficace? Quelles stratégies de prise de notes doit-on favoriser? Ces questions sont importantes pour la réussite scolaire. La prise de notes à l’aide d’outils technologiques a déjà fait l’objet d’études lors de l’intégration d’autres technologies mais peu de recherches se sont intéressées à cette stratégie d’apprentissage avec les tablettes numériques. Un questionnaire a été rempli par des étudiants du secondaire qui utilisent la tablette quotidiennement. L’analyse des résultats montre que les enseignants doivent jouer un rôle actif dans l'appropriation de cet outil.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".