Internal Quality Assurance of the Education Program at Higher Educational Institutions
Bibliographic record
Abstract
Ongoing efforts on internal quality assurance of the educational program at higher educational institutions should be based on comprehensiveness and constant innovative activity. The development of modern and effective ways and measures in order to ensure the quality of educational programs is relevant both for modern higher educational institutions in practice and in the theoretical and methodological plane. The purpose of the research lies in establishing the principles of ensuring the quality of the educational program, which should be applied to achieve high quality teaching following the educational program of higher educational institutions in Ukraine; determining the shortcomings and prospects for the development of educational programs (curricula) and their assessment by educators. In the course of the research, an interpretive qualitative study has been used; along with this, the experiment as the main method, the methods of description, questionnaire and observation have been also used in the academic paper. The research hypothesis lies in the fact that ensuring the quality of the educational program is based on a balanced complex of innovative theoretical principles and their practical implementation. The result of the research is the establishment of the fundamentals for ensuring the quality of educational programs of higher educational institutions, taking into account their innovative nature and the evaluation of the strengths and weaknesses of the curriculum by the participants of the educational process. In the prospect, the implementation of research programs for the further development and improvement of the quality and demand of educational programs of the HEI at the level of the world market of educational services is expected.
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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 | 0.056 | 0.083 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".