Exploring Factors That Influence Technology-Based Distractions in Bring Your Own Device Classrooms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous research on distractions and the use of mobile devices (personal digital assistants, tablet personal computers, or laptops) have been conducted almost exclusively in higher education. The purpose of the current study was to examine the frequency and influence of distracting behaviors in Bring Your Own Device secondary school classrooms. Quantitative and qualitative data were collected from 181 secondary school students (55 female and 126 male) enrolled in three schools across Canada. Almost 80% of the students reported being on task regularly when using mobile devices in class. However, students also engaged in at least one of five distracting activities occasionally or regularly with their mobile devices including emailing (64%), surfing the web (65%), using social media (52%), instant messaging (32%), and playing games (30%). Female students engaged with social media significantly more than male students, whereas male students played games significantly more than female students. Students were rarely distracted by peer use of mobile technology devices. Students were more distracted by their own use of mobile devices when engaged in independent or group work, and less distracted with lectures and student presentations. Students claimed that teacher and school restrictions were probably the most effective method to limit distracting behavior while learning.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it