Evidence map›Paper›PMID 40001742›Full record

ArticleBehavioral sciences (Basel, Switzerland)2025

Endogenesis and Externalization: Configurational Influence of Learning Engagement Among Chinese University Students Majoring in Tourism.

Fenglong Yu, Qian Chen, Bing Hou

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 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.

Fenglong YuSchool of Tourism and Cuisine, Yangzhou University, Yangzhou 225127, China.ORCID 0009-0008-0262-7364
Qian ChenSchool of Tourism and Cuisine, Yangzhou University, Yangzhou 225127, China.ORCID 0000-0003-0050-835X
Bing HouSchool of Tourism and Cuisine, Yangzhou University, Yangzhou 225127, China.

Funding

Yangzhou University Teaching Reform Research Project YZUJX2021-B8Yangzhou University Teaching Reform Research Project YZUJX2023-C16
6 · The paper itself

Abstract

Learning engagement among university students is a critical predictor of academic success. This study, drawing on responses from 333 questionnaires completed by Chinese tourism students, employs the fsQCA method to construct a configurational impact model of learning engagement, exploring the paths and mechanisms of its influence. The study finds that learning engagement among tourism students is shaped by the combined influence of internal and external factors, with internal factors-such as professional cognition, professional evaluations, professional emotions, and academic self-efficacy-playing a foundational and central role. External factors, such as the university environment, provide additional influence, though their impact varies depending on the type of learning engagement. A high level of learning engagement is associated with two distinct configurational paths, identified as the endogenous model and the endogenous-exogenous promotion model. Having positive professional evaluations and a strong professional identity is found to have a significant positive impact on students' academic engagement. Conversely, a low level of learning engagement follows three distinct configurational paths, collectively termed the endogenous suppression model, in which a lack of professional emotions and low academic self-efficacy are key inhibitors of academic engagement. Theoretical and practical implications based on the research findings are also discussed.

Indexed as

Chinaconfigurational influenceinternal and external factorslearning engagementuniversity students majoring in tourism

Identifiers

PMID40001742
PMCPMC11851725

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.