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Record W3137809971 · doi:10.32370/ia_2021_03_15

Features of Implementation in General Educational Institutions Art Programs

2021· article· en· W3137809971 on OpenAlexvenueno aff
Тарас Олефіренко

Bibliographic record

VenueIntellectual Archive · 2021
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Teacher Development
Canadian institutionsnot available
Fundersnot available
KeywordsPaceCreativityThe artsPerceptionProcess (computing)PsychologyRealization (probability)Field (mathematics)Fine artSpiritualityVisual arts educationAestheticsMathematics educationVisual artsComputer scienceArtSocial psychology

Abstract

fetched live from OpenAlex

The article substantiates the psychological and pedagogical features of the development of artistic and creative abilities of junior schoolchildren in Fine Arts. The authors write that the development of creative abilities depends on the learning conditions, the organization of the exercise process, the sequence of learned actions, the transition from simpler to more complex tasks, from slow to fast pace of their implementation. The main tasks of artistic and aesthetic development of junior schoolchildren by means of Fine arts today are: the development of personal integrity, spirituality and consistent formation of aesthetic culture; education of an active attitude to the aesthetic phenomena of reality and art; systematized the formation of skills of aesthetic perception and evaluation activities, stimulation and actualization of creative potential and improvement of practical knowledge, skills and abilities in the field of Fine arts; described the development of the desire for creative self-realization in various types of poly artistic activities.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.032
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.002

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 head0.067
GPT teacher head0.376
Teacher spread0.309 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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