Opinions of the Teaching Staff at Taibah University About Islamic Education Teacher Preparation Programs in the Light of the Requirements of Intellectual Security
Bibliographic record
Abstract
The current study aims to explore the realm of preparing Islamic education teachers in the light of the intellectual security requirements from the point of view of teaching staff at Taibah University. The researcher used the descriptive approach and designed a questionnaire to review the opinions that consisted of two main topics. The first topic is the intellectual security requirements for the academic preparation program (the Specialist Academic Aspect – the Cultural Aspect – the Educational Aspect “Professional”) to encounter radicalism and terrorism. The second topic is the proposed concept to encounter the obstacles to fulfill intellectual security requirements in the preparation colleges programs. Each main topic is subdivided into a set of clauses (42 clauses) for the two topics. The study sample consists of (83) teaching staff members at the preparation colleges. The study has been applied to the study sample during the first semester of the academic year 1439 – 1440 A.H. The study findings show the following: The first topic achieved (78.55%) of the opinions of the study sample members about the preparation program of the Islamic Education teachers in the light of the intellectual security requirements for encountering radicalism and terrorism. The second topic achieved (93%) of the opinions of the study sample members about the proposed concept to overcome the obstacles to meet intellectual security requirements in the preparation programs. There are no differences of the statistical significance level (50. = ∞) among the study sample members toward the questionnaire according to the faculty type for the first topic and the tool in general. There are no differences of the statistical significance level (50. = ∞) among the study sample members toward the questionnaire according to the faculty type for the second topic and the tool in general.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".