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Record W2920045702 · doi:10.5430/wje.v9n1p255

Practicing Mail Art in Visual Arts Course, and Evaluation of the Artworks of Students

2019· article· en· W2920045702 on OpenAlexvenueno aff
Süreyya Genç

Bibliographic record

VenueWorld Journal of Education · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmHappinessVisual arts educationThe artsPsychologyMathematics educationVariety (cybernetics)Course (navigation)Visual artsPedagogyComputer scienceEngineeringArtSocial psychology

Abstract

fetched live from OpenAlex

Purpose of this study is to identify the contribution of the educational use of mail art to Visual Arts Course. Thisstudy has been designed to attain an idea from the activity samples, in order for a more effective and eager teachingof the course. This is a descriptive study based on case study model. The study group consists of 4th-grade studentsfrom a randomly selected elementary school located in Bartın province of Turkey in 2018-2019 school year. Havingbeen carried out with the participation of 43 students, this study is considered significant; as it enables the students tofollow art activities at early ages and introduce them to the concepts of art, artist and process of art-making;emphasizes variety of activities to be applied in visual arts course; and serves as a sample for further researches.Besides, there was no research found on the use of mail art in visual arts course, which makes this study necessary.The study lasted two course hours and the designs of students were collected at the end. Upon consulting expertopinions, designs of the students were subjected to a content analysis in terms of the techniques and objects used, andthe choice of subjects. Then the obtained data were tabulated and interpreted descriptively. Based on the observationsof the researcher, the most remarkable findings of the study are accepted to be the positive effect of planning anactivity different from the regular course format for students; as well as witnessing their enthusiasm, joy, interest,happiness and the authentic works they designed.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.038
GPT teacher head0.371
Teacher spread0.333 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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