Determinants of AI teachers’ behavioural intention to use virtual simulation platforms: an integrated SEM and fsQCA study

The effective realisation of benefits offered by virtual simulation platforms in AI education is contingent upon teachers’ behavioural intentions to adopt such technologies. This study integrates the Technology Acceptance Model (TAM), Social Cognitive Theory (SCT), and Unified Theory of Acceptance and Use of Technology (UTAUT) to examine determinants underlying AI teachers’ behavioural intentions. Analysis of 266 valid responses using Structural Equation Modelling (SEM) demonstrated significant direct effects of perceived usefulness and perceived ease of use on adoption intentions, while platform support (PS), artificial intelligence literacy (AIL), and self-efficacy (SE) exerted indirect influences. Fuzzy-set Qualitative Comparative Analysis (fsQCA) identified five distinct causal configurations sufficient for high behavioural intention. Crucially, AIL and PU formed necessary core conditions across all solutions. These findings offer substantive theoretical contributions and practical guidance for enhancing AI teachers’ platform adoption in K-12 educational contexts.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2026-04-27
DOI
https://doi.org/10.1057/s41599-026-07392-9
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
0.00

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article

Determinants of AI teachers’ behavioural intention to use virtual simulation platforms: an integrated SEM and fsQCA study

Qingchao Ke, Tingting Bao, Siqi Zhang
Humanities and Social Sciences Communications
Technology Adoption and User Behaviour
article

Determinants of AI teachers’ behavioural intention to use virtual simulation platforms: an integrated SEM and fsQCA study

Qingchao Ke, Tingting Bao, Siqi Zhang
article en

Abstract

The effective realisation of benefits offered by virtual simulation platforms in AI education is contingent upon teachers’ behavioural intentions to adopt such technologies. This study integrates the Technology Acceptance Model (TAM), Social Cognitive Theory (SCT), and Unified Theory of Acceptance and Use of Technology (UTAUT) to examine determinants underlying AI teachers’ behavioural intentions. Analysis of 266 valid responses using Structural Equation Modelling (SEM) demonstrated significant direct effects of perceived usefulness and perceived ease of use on adoption intentions, while platform support (PS), artificial intelligence literacy (AIL), and self-efficacy (SE) exerted indirect influences. Fuzzy-set Qualitative Comparative Analysis (fsQCA) identified five distinct causal configurations sufficient for high behavioural intention. Crucially, AIL and PU formed necessary core conditions across all solutions. These findings offer substantive theoretical contributions and practical guidance for enhancing AI teachers’ platform adoption in K-12 educational contexts.

Humanities and Social Sciences Communications
South China Normal University (CN)
National Office for Philosophy and Social Sciences
Quality Education
Openalex Percentile: Top 4%
Technology Adoption and User Behaviour
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