Evidence map›Paper›PMID 42784553›Full record

ArticlePloS one2026

How Generative Artificial Intelligence (GAI) reshapes students' creativity in higher education: A chain path modeling Study from "Exploration-Exploitation" to "Co-Creation-Reflection".

Jie Xu, Yixuan Zeng

Abstract read
In one paragraph

Article in PloS one, 2026. 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

2 authors.

Jie XuInstitute of Creative Arts and Design, UCSI University, Kuala Lumpur, Malaysia.
Yixuan ZengFaculty of Social Sciences and Liberal Arts, UCSI University, Kuala Lumpur, Malaysia.ORCID https://orcid.org/0009-0008-1160-3188

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the widespread integration of Generative Artificial Intelligence (GAI) into higher education, its relationship with students' creativity has become a growing focus of scholarly inquiry. Drawing on data from 424 survey responses and in-depth interviews with eight students, this study constructs and examines a chain path model of Exploration-Exploitation-Co-Creation-Reflection to investigate how GAI-assisted learning processes are associated with students' creativity. Quantitative analyses indicate that exploratory and exploitative behaviors are positively associated with creativity, and these associations are observed alongside perceived cognitive stimulation. Furthermore, co-creation and reflection are significantly associated with flow experience and creative self-efficacy, which are related to students' creative performance. The qualitative findings complement the quantitative results by showing that students' engagement in exploration, knowledge utilization, collaborative co-creation, and reflection during GAI-assisted learning is accompanied by cognitive inspiration and psychological engagement. Overall, this study provides insight into how GAI-assisted learning processes may be associated with creativity development in higher education through the interplay of behavioral, cognitive, and psychological mechanisms, offering implications for educational practice and theoretical advancement.

Indexed as

CreativityGenerative Artificial IntelligenceStudentsAcademiaAdultFemaleHumansLearningMaleSelf EfficacyYoung Adult

Identifiers

PMID42784553
PMCPMC13606950

What OpenQuestion holds

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Registered trials

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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.