Evidence map›Paper›PMID 37496900›Full record

ReviewHeliyon2023

The influence of national policies on the evolution of industrial design education in China.

Shujiang Li, Yusheng Zhang, Zhenya Wang, Hongwen Li

Abstract readReview
In one paragraph

Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shujiang LiDepartment of Industry Design, College of Electromechanical Engineering, Qingdao University of Science and Technology, China.
Yusheng ZhangDepartment of Product Design, College of Art, Qingdao University of Science and Technology, China.
Zhenya WangDepartment of Product Design, School of Mechanical Engineering, Shandong University,China.
Hongwen LiDepartment of Product Design, College of Art, Qingdao University of Science and Technology, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study systematically describes research trends of "industrial design education in China" using bibliometrics mapping from 1992 to 2021. This study aims to sort out industrial design education's historical flow in China and analyze its intrinsic links with Chinese national policies. A combination of quantitative and qualitative methods is used to describe and analyze this study. A technique that combines policy historical analysis with a bibliometric review based on Citespace's knowledge mapping is used in this research. The study was conducted on 492 ″Industrial Design Education" papers included in the core collection database of the China National Knowledge Infrastructure between 1992 and 2021. The results obtained from this study are 1) Research on industrial design education in China has grown steadily over the past three decades and remained high-quality level; 2) The three main research themes are "Chinese culture," "interdisciplinary cooperation" and "government, industry, academia and research" cooperation; 3) Innovation and entrepreneurship, evaluation system, Interdisciplinary, new engineering, and new liberal arts are the research hot spots of Chinese core journals; 4) Interdisciplinary construction in the context of new engineering, assessment system research in the context of high-quality development, and innovation and entrepreneurship education in the context of creative industry development are the future research directions.

Indexed as

BibliometricsCiteSpaceDesign educationIndustrial designPolicy guidelines

Identifiers

PMID37496900
PMCPMC10366391

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.