AI Chatbots in Chinese higher education: adoption, perception, and influence among graduate students—an integrated analysis utilizing UTAUT and ECM models
Искусственный интеллект в виде чат-ботов в высшем образовании Китая: принятие, восприятие и влияние среди магистрантов — интегрированный анализ с использованием моделей UTAUT и ECM
2024-02-07
SCID: 54.1/uv385tqx
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AI ChatbotsConfirmationECMExpectation-Confirmation ModelPersonal innovativenessSatisfactionUTAUTbehavioral intentiongraduate studentshigher educationpartial least squaresstructural equation modeling
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Abstract (AI)
This study is centered on investigating the acceptance and utilization of AI Chatbot technology among graduate students in China and its implications for higher education. Employing a fusion of the UTAUT (Unified Theory of Acceptance and Use of Technology) model and the ECM (Expectation-Confirmation Model), the research seeks to pinpoint the pivotal factors influencing students' attitudes, satisfaction, and behavioral intentions regarding AI Chatbots. The study constructs a model comprising seven substantial predictors aimed at precisely foreseeing users' intentions and behavior with AI Chatbots. Collected from 373 students enrolled in various universities across China, the self-reported data is subject to analysis using the partial-least squares method of structural equation modeling to confirm the model's reliability and validity. The findings validate seven out of the eleven proposed hypotheses, underscoring the influential role of ECM constructs, particularly "Confirmation" and "Satisfaction," outweighing the impact of UTAUT constructs on users' behavior. Specifically, users' perceived confirmation significantly influences their satisfaction and subsequent intention to continue using AI Chatbots. Additionally, "Personal innovativeness" emerges as a critical determinant shaping users' behavioral intention. This research emphasizes the need for further exploration of AI tool adoption in educational settings and encourages continued investigation of their potential in teaching and learning environments.
Key Findings
1
A combined UTAUT-ECM model with seven substantial predictors was constructed to predict graduate students' intentions and behavior toward AI Chatbots.
2
ECM constructs, especially Confirmation and Satisfaction, exert stronger influence on users' behavior than UTAUT constructs.
3
Perceived Confirmation significantly influences Satisfaction and subsequent continuance intention to use AI Chatbots.
4
Personal innovativeness is a critical determinant shaping users' behavioral intention to use AI Chatbots.
5
Seven out of eleven proposed hypotheses were validated, indicating partial support for the integrated model.
6
Survey data from 373 Chinese graduate students were analyzed using PLS-SEM to validate the model's reliability and validity.
7
The study highlights the need for further research on AI tool adoption and their potential roles in higher education teaching and learning.
Research Object
AI Chatbot technology used by graduate students in Chinese higher education
Research Subject
Determinants of acceptance, satisfaction, attitudes, and continued behavioral intention to use AI Chatbots (influence of UTAUT and ECM constructs such as Confirmation, Satisfaction, and Personal Innovativeness)
Publication Details
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2024-02-07
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References available in scid.ai8
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