The Value and a Preliminary Study of the Integration of Traditional Chinese Painting and Calligraphy & Modern and Contemporary Art in Primary School Art Teaching
Bibliographic record
Abstract
Finding a unique way to help students better accept between traditional Chinese Painting and Modern and Contemporary Art is an increasing concern in primary school art teaching. The purpose of this study is to investigate fine art education field according to analyze the current situation of Chinese traditional painting and calligraphy together with Modern and Contemporary Art in the art curriculum of primary schools: shallow embedded curriculum, shortage of Class Hours and relatively simple teaching method. Based on the key competence of the disciplines, it discusses the value of integrating those two in art teaching of primary schools, proposes a Bridge to connect the Chinese painting and calligraphy& Modern and contemporary art and provides a curriculum construction model that connects the artistic language with the concept of disciplines. This study takes the work of artist A.R.Penck as the theme, starting from the big idea, looking for basic problems, designing a curriculum with the integration of two kinds of art forms, and teaching practice at The China Soong Ching Ling Science & Culture for Young People. This study not only answers the feasibility of the curriculum construction model but also gives some critical thinking about it.
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 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".