A Suggested Proposal to Develop Distance Learning Programs in Border Schools in the Kingdom of Saudi Arabia
Bibliographic record
Abstract
The aim of this research is to find a proposed vision for developing distance education programs in border schools in the Kingdom of Saudi Arabia, and to explore the reality of the proposed educational programs for developing distance education programs. In order to achieve the research objectives, the descriptive and analytical approach was used for its suitability for this research, as the questionnaire was used as a research tool. The research sample consisted of (150) female teachers from border schools. The results of the research revealed that the reality of female teachers ’practice on distance learning programs in border schools in the Kingdom of Saudi Arabia is central. And that the use of technology is the most important requirement for developing distance education programs in border schools from the Kingdom of Saudi Arabia. The results also showed the achievement of leadership in diversifying and developing teaching and learning methods through the distance education system based on employing modern information and communication technology, equipping schools with all technological equipment, and supporting students with modern equipment and teachers with modern training to achieve the goals of distance education. In light of the results, the research paper presented a proposal for developing distance education programs in border schools in the Kingdom of Saudi Arabia.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".