Opinions of Faculty Members Regarding Quality Implementation in the Faculty of Arts at King Saud University
Bibliographic record
Abstract
King Saud University has been seeking to achieve excellence and leadership; this is shown through seeking to advance towards the best and to cope with the universities needs by qualifying its employees academically and practically in various fields. Throughout this journey of excellence, King Saud University has adapted the quality system implementation in 2007.This study aims at presenting the opinions and suggestions of faculty members regarding quality implementation mechanisms in the departments of Faculty of Arts at King Saud University. To achieve the goals of the current study, the researchers depend on a questionnaire, which was constructed by both of them to collect data. This tool was constructed based on the standards steps of constructing a questionnaire. The tool has included several focus points which are: social and academic characteristics of the study community that consists of faculty members (n=273), strategies (vision, mission, and goals) which include 8 statements, evaluation which includes 14 statements, and finally communication and engagement which include 5 statements. In light of the results of this study the researchers recommend considering the goals of Quality Units in the departments of Faculty of Arts so that they agree and serve the goals of the development process and the quality in the college and the university, in addition to introducing a clear and announced plan of quality to all employees in the department. In addition, they suggest that Quality Units in the departments of Faculty of Arts should hold training workshops and courses to clarify quality requirements and ensures that they are understood by the employees.
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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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".