Evidence map›Paper›PMID 40618006›Full record

ArticleScientific reports2025

Generative artificial intelligence in entrepreneurship education enhances entrepreneurial intention through self-efficacy and university support.

Yingying Xie, Shaofeng Wang

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. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. 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

2 authors.

Yingying XieSchool of Innovation and Entrepreneurship, Zhejiang Wanli University, Ningbo, 315100, China.
Shaofeng WangInternational Business School, Fuzhou University of International Studies and Trade, Fuzhou, 350202, China. vipwhsl@hotmail.com.ORCID http://orcid.org/0000-0002-0300-2453

Funding

Zhejiang Province Education Science Planning 2023 General Planning Project 2023SCG399
6 · The paper itself

Abstract

This study investigates how Generative Artificial Intelligence Supported Entrepreneurship Education (GAISEE) influences university students' entrepreneurial intentions through a quantitative analysis of Chinese higher education institutions. Using structural equation modeling with data from 346 university students, we demonstrate that GAISEE significantly enhances both entrepreneurial self-efficacy (β = 0.523, p < 0.001) and entrepreneurial intention (β = 0.244, p < 0.001). The research reveals that entrepreneurial self-efficacy mediates the relationship between GAISEE and entrepreneurial intention, while the university entrepreneurial environment moderates these relationships. Notably, an optimized university environment strengthens the positive effects of GAISEE on both entrepreneurial self-efficacy (β = 0.333, p < 0.001) and entrepreneurial intention (β = 0.207, p < 0.001). These findings provide empirical evidence for the effectiveness of integrating generative AI technology in entrepreneurship education and highlight the importance of supportive university ecosystems in fostering student entrepreneurship.

Indexed as

Entrepreneurial intentionEntrepreneurial self-efficacyEntrepreneurship educationGenerative artificial intelligenceUniversity entrepreneurial environment

Identifiers

PMID40618006
PMCPMC12228775

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.