Study Benefits of Smartphones: Perceptions of Female Emirati Pre-Service Teacher Undergraduates
Bibliographic record
Abstract
Smartphones are becoming ubiquitous and can be very useful study tools. We explored female Emirati undergraduates’ perceptions of smartphone use in the classroom. Furthermore, we investigated the age at which participants received their first smartphones, the number of smartphones to which they had access at the time of the study, and the influence of these aspects on the use of smartphones as a learning tool. An online survey of 189 participants revealed that the age of receiving their first smartphone, combined with the number of smartphones they owned or had access to at the time of the study, did not correlate with their perceptions of the usefulness of smartphones as a learning tool in a statistically significant manner. However, participants in their first year of study had fewer positive perceptions about the use of smartphones in the classroom than participants in subsequent study years. We surmise that this might be attributable, in part, to the further experiences older students have had or classes they have taken or to student teaching experiences in which they might have firsthand observed the benefits of phone use in the classroom as a learning tool.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".