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Record W2923776614 · doi:10.32370/ia_2019_01_18

Printed Graphics in the Educational Process of Training the Artist Pedagogue

2019· article· en· W2923776614 on OpenAlexvenueno aff
Ivan Oros

Bibliographic record

VenueIntellectual Archive · 2019
Typearticle
Languageen
FieldComputer Science
TopicInnovative Educational Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsGraphicsProcess (computing)Computer scienceMathematics educationCreativityRestructuringComprehensionMultimediaCreative briefPedagogyPsychologyPolitical scienceComputer graphics (images)

Abstract

fetched live from OpenAlex

In the article the discipline "Printed Graphics" is considered and its creative possibilities and its role in educational process of training of future artists-teachers are revealed. It is noted that one of the priority tasks defined by the National Doctrine of Pedagogical Education Development in Ukraine is the creation of preconditions for the education of a teacher -a person capable of creative thinking, to take non-standard creative decisions on their own, to flexibly respond to changes in conditions of restructuring the aesthetic sphere of society. It turns out that modern practice demonstrates the lack of a comprehensive study of printed graphics as a specific discipline in the system of artistic education in the process of forming an artist-teacher. The stated purpose of the study is the need to disclose the creative possibilities of print graphics and its role in the educational process and to identify the territorial and methodological principles of training the artist -the teacher through means of printed graphics.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0060.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.045
GPT teacher head0.320
Teacher spread0.274 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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