Examining Pre-Service Teachers’ Nomophobia Levels in Terms of Several Variables
Bibliographic record
Abstract
This study aims to determine the nomophobia levels of pre-service teachers, the variables affecting their nomophobia levels, and the relationship between the levels of nomophobia and cyberloafing. The study, which was designed as a correlational study, was conducted with the voluntary participation of 666 pre-service teachers. The data of the study were collected using a personal information form, the Nomophobia Scale (NMP-Q), and the Cyberloafing Scale. The results showed that 528 students (79.3%) had a moderate and high level of nomophobia while 138 students (20.7%) had a low level of nomophobia. As a result of the analyses conducted to determine whether the nomophobia levels of teacher trainees differed depending on gender, it was seen that the nomophobia level of women was statistically higher than that of men. It was concluded that the nomophobia levels of the pre-service teachers did not vary depending on the level of education and their experience of using smartphones. Although, the results gathered from the first analysis results indicated that the nomophobia levels of the pre-service teachers depicted difference concerning the departments at which they studied, this difference proved insignificant as indicated by the anteceding detailed analyses carried out. It was concluded that the nomophobia levels of the pre-service teachers differed significantly depending upon the amount of time they spend on social media. The last finding of the study concluded that cyberloafing significantly predicted nomophobia levels of pre-service teachers. Based on this result, it can be said that the pre-service teachers’ cyberloafing behaviors will increase their tendency to exhibit nomophobic behaviors. For further research, mixed studies in which qualitative methods will also be used to obtain more in-depth data can be designed. It was also found out that the nomophobia levels of the pre-service teachers differed significantly based on their daily social media usage time.
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 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".