Bibliographic record
Abstract
In terms of design education, majority of education institutions in China have adopted cramming method of education for a long period of time and does not proactively utilize the creative design education method of the West. This study aims to propose creative character education measures based on academic theory consideration concerning character and talented people in order to identify measures for revitalizing creative design education equipped with upright character. Daniel Pink suggested 6 conditions of future-type of talented person and proposed creative character education measures of design education required in the current era by analyzing the arts and culture education in Canada, Finland and UK. In such process, it implies how import the national policies are for creative character education and in addition, demonstrates the effect of design education on a nation's economic effects and cultural status. On the basis of this research, it is urgent to change the stagnation of China design education, which is limited to imitating developed countries' educational models. In order to make full use of the following six theoretical conditions of humanistic creative design education, it is important to apply flexibly the six conditions of Branding, Storytelling, Communication, Thinking, Experience and Value to teaching. This is a showcase of the new methodology of China design education and provide a new methodology of China design education.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.018 |
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; both teacher heads agree on what is shown here.
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".