Teachers and Technology: Trends in English Language Teaching in Saudi Arabia
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
Technology has impacted the learning approaches and vice-versa with an aim to improve the standards of language teaching/learning process. The present study focuses on teachers’ preferences and use of technology in their language classrooms. A survey was conducted to seek opinion of EFL teachers both male and female at the English language center on technology-related competencies. The survey comprised four domains: planning and preparation, classroom management, instruction, and professional responsibilities (Danielson, 2007).The questionnaire was distributed to 100 English language teachers (50 males and 50 females) at Taif University English Language Centre. The responses revealed that most of the teachers thought aware of the technology and its uses in education don’t integrate technology in their teaching at planning and preparation stage. They use the available technological gadget in the classroom to exploit some of the activities. They must use the university LMS for uploading certain activities and assessment otherwise they hesitate to design technology-based activities for English language learners. They and the students need training in integrating technology with teaching and learning process.
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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 | 0.104 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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