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Record W3047341257 · doi:10.5430/ijhe.v9n7p119

The Objectives and Practical Aspects of Quality Assurance System of Higher Education

2020· article· en· W3047341257 on OpenAlexvenueno aff
Dora Ivanova, Olga V. Goray, Nadiia I. Horbachova, Iryna M. Krukovska, Svitlana D. Poplavska

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsQuality assuranceHigher educationQuality (philosophy)European unionOrder (exchange)Presentation (obstetrics)Comparative educationBusinessPolitical scienceMedical educationEconomic growthMarketingEconomicsMedicineService (business)FinanceInternational trade

Abstract

fetched live from OpenAlex

Each country in the world has its own individual approaches to the quality assurance system of higher education, so the quality of educational services in each country is different. The developing countries should be guided by the standards and recommendations put forward by the world’s leading countries in the field of the assurance system of higher education in order to improve the quality of education services. The purpose of the scientific investigation is to formulate the objectives and analyze the practical aspects of functioning of the quality assurance system of higher education. In the study’s framework of the practical aspects of the higher education’s quality in European Union’s countries, the methods of general analysis have been used, including comparison and grouping; at the same time, the presentation of statistics is also demonstrated by graphical methods. The practical aspects of quality assurance of higher education in European Union’s countries have been analyzed, which is reflected in the dynamics of the number of students who have received higher education, the structure of higher education degree seeking applicants, the employment rate of graduates who have graduated from higher education institutions (Employment rates of recent graduates), the World University Rankings, the Europe Teaching Rankings, rating of the strength of the higher education system (the QS Higher Education System Strength Rankings). Proposals for ensuring the proper quality of higher education and a high level of educational services to educational institutions of the European Union have been presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.917
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.406
Teacher spread0.377 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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