Student communication and study habits of first-year university students in the digital era | Communication étudiante et habitudes d’étude des étudiants universitaires de première année à l’époque numérique
Bibliographic record
Abstract
This paper reports on research into how first-university students communicate with peers and professors and their general study habits and to examine the possible relationship between students’ use of digital technologies. The research is positioned in the interpretive paradigm. We conclude that most students feel comfortable with digital technologies and they see Facebook/MySpace as more about connecting and interacting with friends than for academic communication. Results show that students prefer face-to-face communication for both academic/school and social communication. Regarding study habits, students prefer to learn by themselves, work independently and to study at home. Cet article présente la recherche sur les habitudes d’étude des étudiants universitaires, leur usage des technologies numériques et leur façon de communiquer entre eux et avec leurs professeurs. Nous concluons que la plupart des étudiants se sentent à l’aise avec les technologies numériques et qu’ils utilisent les médias sociaux pour leurs liens et interactions avec leurs amis plutôt que pour la communication scolaire. Les étudiants préfèrent les communications en personne en ce qui a trait aux communications scolaires et sociales et préfèrent apprendre par eux-mêmes, travailler de manière autonome et étudier à la maison.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".