Model Development for Internal Quality Assurance in Guangxi Vocational Colleges
Bibliographic record
Abstract
The study aimed to 1) examine components of the Internal Quality Assurance (IQA) system in higher vocational colleges in Guangxi, China, 2) assess the current state, desired state, and priority needs of the IQA system, and 3) develop a model for the IQA system. The research began with a synthesis of academic sources and policy documents, which five experts evaluated. Questionnaires were then developed based on nine components of the IQA system and distributed to 306 participants involved in quality management, including QM/QA experts. The findings revealed that the current IQA system was at a moderate level, while the desired state was significantly higher. The Priority Need Index (PNImodified) indicated urgent needs in the Criteria, Operation, and Objective systems. The proposed IQA model was constructed from literature reviews and consisted of seven components: Concepts, Principles, Objectives, Contents, Approaches, Procedures, and Evaluation. By integrating the findings on system components, current and desired states, and key needs, the study developed a comprehensive IQA model. The model’s suitability and feasibility were validated by five experts and found to be of a very high level. The study concluded with recommendations for practical implementation and directions for future research.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".