Practicability of Application of Re-Engineering the Administrative Processes at Colleges of Education in Universities in Arab-Majority Countries
Bibliographic record
Abstract
The study aims to highlight the importance of considering the implementation of process of re-engineering Reengineering Administrational Processes (RAP) in the Arab countries universities, particularly, colleges of education to attain good educational outputs. It seeks to highlight the requirements for this implementation and explore the problems associated to the implementation it and distinguish themselves from other organizations is. The Process of Re-Engineering (RAP) is defined as a rapid and drastic re-designing of managerial and strategic process of values at colleges of education in the Arab States Universities in order to attain good educational outputs. The managerial process includes planning, organization, control, follow-up, evaluation and decision taking. The significance of the study is that it can considerably help improve administrative processes applied in the domain of strategic planning at colleges of education in Arab States. The main objective of the study was to outline the main demands of colleges of education for using (RAP) and the obstacles that face its application. For that purpose, the descriptive/ analytic method was used. The study relied heavily on the analysis of the available literature, writings, and publications on the topic, for predicting the practicability of applying RAPRAP. The study came up with the following main results: RAP application, if used properly, can raise the level of job satisfaction among staff members of Arab States colleges of education in particular and the Arab States Universities in general. RAP application can affect total amendments on colleges of education administrative systems for better rendered services. The most demanding requirements of RAP are those that directly relate to the organization structure of the particular corporation, and all its activities for more flexibility, speed and accuracy of performance. The basic human requirements for RAP application include effective training for trainers for the sake of radical change in concepts and ideas. The main obstacles that face RAP application include the poor outcome at colleges of education regarding teaching/learning process, in addition to poor strategic information management on the part of colleges of education and universities. RAP is not fully made use of, despite large sums of money having been spent on for that exact purpose.
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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 | 0.037 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".