ArticleFrontiers in psychology2025
Exploring AI tool adoption in higher education: evidence from a PLS-SEM model integrating multimodal literacy, self-efficacy, and university support.
Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Exploring College Students' AI Dependence in Human-AI Collaborative Creation: Development and Validation of the CC-PACE Model.Journal of Intelligence · 2026Article
- Latent profiles of college students' AI literacy and their association with AI acceptance: the sequential indirect role of perceived affordances and growth mindset.Frontiers in psychology · 2026Article
- Multidimensional perceived school support and AI learning anxiety among university students: the mediating roles of control-value appraisals.Frontiers in psychology · 2026Article
- The influence of designer identity on design majors' intention to use AIGC tools: an SEM-fsQCA analysis in China.Frontiers in psychology · 2026Article
- The influence of perceived AI capability on learning engagement in smart education environments: the mediating role of academic self-efficacy and the moderating role of teacher-student relationship.Frontiers in psychology · 2026Article
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3 authors.
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Abstract
Introduction: Framed within the technology acceptance model, this study examines how multimodal literacy, self-efficacy, and university support affect students' attitudes toward artificial intelligence tools and the students' intentions to adopt them. Methods: Survey data from 498 students were analyzed using PLS-SEM 4.0 and SPSS 29. Results: The findings showed that the perceived usefulness of the AI tools was the strongest predictor of both attitude toward the tools and intention to use them. All three antecedent variables (multimodal literacy, self-efficacy, and university support) significantly impacted perceived usefulness and perceived ease of use. Discussion: By integrating individual dimensions and also institutional dimensions into the technology acceptance model, this study offers fresh insight into how AI tools might take root more effectively in higher education.
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