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Record W4353083195 · doi:10.5430/jct.v12n2p38

Innovation of the Educational Process in Early Childhood Education Institutions

2023· article· en· W4353083195 on OpenAlexvenueno aff
Iryna Danylchenko, Ореста Карпенко, Mariya Chepil, Zoriana Vakolia, Liudmyla Vrochynska

Bibliographic record

VenueJournal of Curriculum and Teaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Professional Development
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)IdealizationField (mathematics)Early childhood educationEngineering ethicsEarly childhoodPedagogyMathematics educationSociologyPsychologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Nowadays, the introduction of the latest means of development of early childhood education institutions is connected with the general trends of innovation processes in the economy and new social standards. The publication of new textbooks, and manuals, as well as equipping higher pedagogical education institutions with computer technology should meet the requirements of the development of new material bases and the challenges of professional development of early childhood teachers. Under such requirements, the goals, content, conditions, and expected consequences of the innovative development of the educational process in early childhood education institutions are being developed. The article aims to characterize the main directions and features of scientific research in the field of innovative development of the educational process carried out in early childhood education institutions. In the course of organizing and conducting both theoretical and practical components of this study, the analytical and bibliographic method was applied to study the scientific literature on the educational process in early childhood education institutions. Analysis, synthesis, induction, and deduction were employed in the processing of scientific information. System-structural, comparative, logical, and linguistic methods, abstraction, and idealization were used to study and process data. Moreover, the questionnaire survey served in the practical establishment of certain aspects of innovative processes in the field of education in preschool institutions. Based on the results of the study, the theoretical aspects of innovating the process of upbringing in preschool education have been studied. Moreover, the most essential factors, stages, and components of this process from the standpoint of its subjects have been 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)0.007
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0030.006
Scholarly communication0.0070.005
Open science0.0010.003
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 head0.026
GPT teacher head0.385
Teacher spread0.359 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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