A Prospected Scenario for Developing the Teaching of Islamic Education Courses in Colleges of Education in the Light of the Requirements of Distance Education
Bibliographic record
Abstract
The current study aimed to uncover the views of faculty members on teaching Islamic education courses in colleges of education in light of the requirements of distance education, and to build a proposed conception for the development of teaching these courses. The study sample consisted of (92) members of the faculty of the Faculties of Education in Saudi universities who were chosen by the random cluster method, and to achieve the objectives of the study, the researcher constructed a questionnaire consisting of (66) paragraphs within (4) axes and the validity and stability of the questionnaire was verified. Then the research data were collected and analyzed, and the results showed: that the opinions of faculty members about teaching Islamic education courses in light of the requirements of distance education came first within the focus of the course objectives, then the axis of evaluation and its tools came in the second rank, then the axis of educational activities and teaching methods and finally Course content focus. The results also showed that there are no statistically significant differences between the opinions of faculty members "attributed to the variable of gender and experience in university teaching." And in light of these results, the researcher presented a proposed scenario for the development of teaching Islamic education courses in the light of distance education.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| 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".