Evidence map›Paper›PMID 41272010›Full record

ArticleScientific reports2025

Research on the emerging technological intervention models in design education from a strategic perspective of global design education institutions.

Fan Chen, Zhongjie Lin, Xiang Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Fan ChenTongji University, Shanghai, China. chenfantj@foxmail.com.
Zhongjie LinUniversity of Pennsylvania, Philadelphia, USA.
Xiang LiZhejiang University of Technology, Hangzhou, China.

Funding

China Postdoctoral Science Foundation GZC20231938
6 · The paper itself

Abstract

With the rapid advancement of emerging technologies, design education is undergoing a model transformation. This study employs a mixed-methods approach that combines semantic textual analysis with semi-structured interviews, which aims to examine the development strategies of 71 design education institutions worldwide to systematically analyze the pathways through which technologies such as Artificial Intelligence (AI), Virtual and Augmented Reality (VR/AR), Big Data, and Robotics are integrated into design education. Four major models of intervention are identified: lab-driven innovation, industry incubation, interdisciplinary fusion, and curriculum integration. The research reveals that emerging technologies primarily intervene in areas such as instructional support, pedagogy, and curriculum structure, while remaining underrepresented in strategic dimensions such as regional distribution of DEIs, degree types, and stakeholder types. It also highlights key challenges including resource disparity, lack of accreditation frameworks, overreliance on technology, and ethical risks. In response, it proposes strategic solutions such as regional resource sharing, modular accreditation systems, human-AI collaborative teaching, industry-driven curriculum optimization, and ethical governance of technology.

Indexed as

Design educationDesign education institutionsEmerging technologiesIntervention modelsStrategic planning

Identifiers

PMID41272010
PMCPMC12639016

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.