Students’ use of information and communication technologies in the classroom: Uses, restriction, and integration
Bibliographic record
Abstract
Research has frequently found that students use their information and communication technologies—such as smartphones and laptops—for non-academic uses in the classroom. These uses include sending messages as well as checking email and social media accounts. This study aimed to examine students’ in-class information and communication technology use, their motivations for it, and perceptions of it, as well as their attitudes toward restriction and integration of information and communication technologies in the classroom. It was found that students most frequently engage in non-academic information and communication technology use when they feel that they would not miss any new class content, or when they feel disengaged. Students perceived that their non-academic information and communication technology use had costs, especially distraction. However, students also reported negative attitudes toward policies that would restrict their information and communication technology use in the classroom but had positive perceptions of attempts to integrate information and communication technology use. We propose that information and communication technology integration can be an effective method of increasing student engagement—and therefore decreasing non-academic information and communication technology use.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".