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Record W4312117470 · doi:10.5430/jct.v11n9p40

Implementation of Quality Control of the Educational Process in Higher Education Institutions Based on Models

2022· article· en· W4312117470 on OpenAlexvenueno aff
Ihor Kolodii, Iryna Piatnytska, Alona Shkodyn, Kostiantyn Herasymiuk, Н. А. Пономаренко

Bibliographic record

VenueJournal of Curriculum and Teaching · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor Market and Education
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Quality (philosophy)Higher educationControl (management)Relevance (law)UkrainianField (mathematics)Order (exchange)Computer scienceManagement scienceAdaptabilityKnowledge managementEngineering ethicsProcess managementPolitical scienceBusinessEngineeringArtificial intelligenceManagementEpistemologyMathematics

Abstract

fetched live from OpenAlex

Modern Ukrainian society is in a complex process of transformation in various spheres at the present stage of its historical development, including, in the field of education. The humanitarian development of the country and the world sets new tasks for the national education system, the solution of which is inefficient within the framework of the existing methodology. Currently, the issue of analysing the efficiency of the higher education system and its adaptability in the field of training specialists of various profiles to constant and changing processes in various spheres of the society is of particular relevance. The inconsistency of the scientific-theoretical and scientific-practical level of the quality control model of higher education has determined the problem of the necessity to analyse the existing models in order to improve their individual aspects. The purpose of the academic paper is to study the existing models of quality control of the educational process in higher education and to clarify the practical features of the development of such models from the perspective of participants in the learning process in higher educational institutions. Methodology. In the course of the research, the analytical-bibliographic method was used to study the scientific literature on the issues of quality control of the educational process in higher educational institutions, as well as a questionnaire survey in order to clarify in practice the certain aspects of developing the models for the quality management of education in higher educational institutions. Results. Based on the results of the research, the features of implementing the individual models of quality control of the educational process in higher educational institutions were studied, and the main principles and characteristics that should be taken into account when developing such a model for each individual institution of higher education were clarified.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.004
Scholarly communication0.0090.005
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.330
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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