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Record W4224301283 · doi:10.32370/ia_2022_03_11

Distance Learning of Physical Education as a Component of the System of Modern Education within the Framework of the "New Ukrainian School" Reform

2022· article· en· W4224301283 on OpenAlexvenueno aff
Olena Voichun, Vira Molotylnikova

Bibliographic record

VenueIntellectual Archive · 2022
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Training Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianCompetence (human resources)Distance educationPluralism (philosophy)SociologyMathematics educationPedagogyEngineering ethicsPolitical sciencePsychologyEngineeringEpistemology

Abstract

fetched live from OpenAlex

The deals with the features of the formation of key competencies of the educational reform "New Ukrainian School" in the process of distance learning of physical culture. The ways of realization of each key competence during the lesson of physical training and other forms of physical education are described. The attention is focused on educational resources, with the help of which it is possible to introduce any competence into the practice of secondary education institutions at the present stage. Distance learning in the modern sense has been formed relatively recently and, therefore, it focuses on the advanced methodological experience accumulated by various educational institutions of the world space, on the use of the latest and operational pedagogical technologies to meet demands of modern education and social security. Certainly, the definition of ‘distance learning’ is characterized by a pluralism of definitions, which indicates a wide range of approaches to its interpretation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.370
Teacher spread0.342 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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