Practicing Mail Art in Visual Arts Course, and Evaluation of the Artworks of Students
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".