ArticleFrontiers in psychology2022
Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory.
Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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25 citing papers in PubMed.
- Article
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- Educational anxiety and student mental health in the era of artificial intelligence: a multi-source data fusion analysis in smart education.Frontiers in public health · 2026Article
- Determinants of acceptance and usage of generative AI among Chinese medical students: a UTAUT-based empirical investigation.Frontiers in psychology · 2026Article
- A Systematic Review of User Attitudes Toward GenAI: Influencing Factors and Industry Perspectives.Journal of Intelligence · 2025Review
- Factors influencing digital media designers' subscription to premium versions of AI drawing tools through a mixed methods study.Scientific reports · 2025Article
- Factors Influencing College Students' Generative Artificial Intelligence Usage Behavior in Mathematics Learning: A Case from China.Behavioral sciences (Basel, Switzerland) · 2025Article
- What is the influence of psychosocial factors on artificial intelligence appropriation in college students?BMC psychology · 2025Article
- Determinants of rural middle school students' adoption of AI chatbots for mental health.Frontiers in public health · 2025Article
- Quantum psychology approach on enjoyment as mediator in relationship between L2 flow and engagement.Frontiers in psychology · 2025Article
- Factors influencing learners learning interest when using AI chatbots-assisted math leaning in higher education.Frontiers in psychology · 2025Article
- Article
- Mindfulness and AI adoption: extending the technology acceptance model for Chinese media students.Frontiers in psychology · 2025Article
- From Acceptance to Dependence: Exploring Influences of Smart Healthcare on Continuous Use Intention of Mobile Health Services Among Older Adults with Chronic Illnesses in China.Behavioral sciences (Basel, Switzerland) · 2024Article
- Utilization of, Perceptions on, and Intention to Use AI Chatbots Among Medical Students in China: National Cross-Sectional Study.JMIR medical education · 2024Article
- Acceptance of artificial intelligence in university contexts: A conceptual analysis based on UTAUT2 theory.Heliyon · 2024Review
- Factors That Affect the Acceptance of Educational AI Tools by Greek Teachers-A Structural Equation Modelling Study.European journal of investigation in health, psychology and education · 2024Article
- From literacy to learning: The sequential mediation of attitudes and enjoyment in AI-assisted EFL education.Heliyon · 2024Article
- Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective.Heliyon · 2024Article
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4 authors.
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Abstract
Artificial intelligence (AI) technology has been widely applied in many fields. AI-assisted learning environments have been implemented in classrooms to facilitate the innovation of pedagogical models. However, college students' willingness to accept (WTA) AI-assisted learning environments has been ignored. Exploring the factors that influence college students' willingness to use AI can promote AI technology application in higher education. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and the theory of perceived risk, this study identified six factors that influence students' willingness to use AI to analyze their relationships with WTA AI-assisted learning environments. A model including six hypotheses was constructed to test the factors affecting students' WTA. The results indicated that college students showed "weak rejection" of the construction of AI-assisted learning environments. Effort expectancy (EE), performance expectancy (PE), and social influence (SI) were all positively related to college students' WTA AI-assisted learning environments. Psychological risk (PR) significantly negatively influenced students' WTA. The findings of this study will be helpful for carrying out risk communication, which can promote the construction of AI-assisted learning environments.
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