Student Perceptions of Using Tablet Technology in Post-Secondary Classes / Perceptions des étudiants quant à l’utilisation des tablettes électroniques dans les classes universitaires
Bibliographic record
Abstract
This paper assesses students’ attitudes towards using tablets, such as the Apple iPad, in university classes. Tablets are found to be a substitute for laptop computers. Students initially expressed a great deal of optimism regarding the technology, and, although their views diminished slightly as they gained experience with using a tablet, their attitude towards the technology remained overwhelmingly positive. Most students experienced an easy transition from using a laptop to using a tablet. Furthermore, once students adopted the tablets in place of their laptops for in-class use, the types of tasks they performed with the tablets differed from the types of tasks they had previously performed with the laptop. Overall, the tablets reduced the incidence of off-task behaviour during lectures such as using chat and social networking applications. Cet article évalue les attitudes des étudiants quant à l’utilisation de tablettes électroniques telles que le iPad d’Apple dans les classes universitaires. Les tablettes sont considérées comme des substituts aux ordinateurs portables. Les étudiants ont d’abord exprimé beaucoup d’optimisme à l’égard de cette technologie, et bien que leur perception se soit légèrement dégradée avec l’expérience de la tablette, leur attitude envers la technologie est restée très positive. La plupart des étudiants ont effectué une transition facile entre l’utilisation d’un ordinateur portable et celle d’une tablette. En outre, une fois que les étudiants ont adopté en classe les tablettes à la place de leurs ordinateurs portables, les types de tâches qu’ils accomplissaient avec les tablettes ont différé des celles qu’ils effectuaient précédemment avec l’ordinateur portable. Dans l’ensemble, les tablettes ont réduit les cas de comportements hors tâche durant les cours, comme l’utilisation du tchat et des réseaux sociaux.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".