Integration of Technology among Saudi EFL Teachers
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
In the field of education, technology is currently considered a new trend. This study aims to examine the factors that affect the integration of new technologies in EFL classrooms. Factors considered include teacher’s age, teacher’s level of technological proficiency, and teacher’s perception of technology. To achieve this, the study involved a questionnaire consisting of 21 items and a total of 38 Saudi EFL teachers participated in it. The results indicate that there is no significant relationship between teacher age and technology integration. However, both teachers’ level of proficiency in technology and teacher’s perception of technology were significantly related to technology integration in Saudi EFL classrooms. It is recommended to provide teachers with professional development and support in technology integration and to supply classrooms with resources such as computers and smart boards. 
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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