Application of Saudi’s National qualifying Framework in System Analysis & Design Course
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
In higher education, research on quality assurance is one of the prominent fields at present. The National Qualifications Framework (NQF) is an important element in accreditation and quality assurance system in the Kingdom of Saudi Arabia. It is designed by National Commission for Academic Accreditation and Assessment (NCAAA) to ensure that the quality of higher education is equivalent to high international standards. In Saudi Arabia, quality assurance is still a relatively new concept and the Saudi universities seem not to effectively implement it because of certain obstacles. Curriculum development using NQF is one of the core and challenging contexts in quality assurance. This paper presents an application of Qualification Framework in curriculum development for system analysis and design course at Jazan University in Saudi Arabia. The objective of the research shall be to present a model course after applying NQF standards. The research shall begin with identification of the problems, finding out the reasons and to present a model curriculum. The research shall include a literature review. The method of research shall be descriptive, empirical and qualitative approach. Document analysis – mainly NCAAA guides and brainstorming interactions with the educators shall be used as a research instrument. The paper is expected to help educators in better planning of their course learning outcomes and most importantly helps in mapping the assessment methods and questions. This will also help to assess and ensure that the graduates’ knowledge level and skills acquired are as defined in the learning outcomes in the curriculum. The educators can use this paper as a model to apply NQF for the curriculum development of other courses at higher education level.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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