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Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model
by
Li, Kang
in
Academic achievement
/ Analysis
/ Artificial intelligence
/ Attitudes
/ Behavior
/ College students
/ Distance learning
/ Educational aspects
/ Hypotheses
/ Independent study
/ Influence
/ Motivation
/ Online instruction
/ Public health
/ Teaching
/ Technology
/ Technology Acceptance Model
/ Technology adoption
/ Technology application
2023
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Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model
by
Li, Kang
in
Academic achievement
/ Analysis
/ Artificial intelligence
/ Attitudes
/ Behavior
/ College students
/ Distance learning
/ Educational aspects
/ Hypotheses
/ Independent study
/ Influence
/ Motivation
/ Online instruction
/ Public health
/ Teaching
/ Technology
/ Technology Acceptance Model
/ Technology adoption
/ Technology application
2023
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Do you wish to request the book?
Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model
by
Li, Kang
in
Academic achievement
/ Analysis
/ Artificial intelligence
/ Attitudes
/ Behavior
/ College students
/ Distance learning
/ Educational aspects
/ Hypotheses
/ Independent study
/ Influence
/ Motivation
/ Online instruction
/ Public health
/ Teaching
/ Technology
/ Technology Acceptance Model
/ Technology adoption
/ Technology application
2023
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Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model
Journal Article
Determinants of College Students’ Actual Use of AI-Based Systems: An Extension of the Technology Acceptance Model
2023
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Overview
Acceptance of, behavioral intention towards, and actual use of AI-based systems or programs has been a topic of growing interest in the field of education. A considerable number of studies has been conducted to investigate the driving factors affecting users’/students’ intentions regarding certain technology or programs. However, few studies have been performed to understand college students’ actual use of AI-based systems. Moreover, the mediating effect of students’ learning motivation was seldom considered. Therefore, the present study was conducted to explain factors contributing to college students’ actual use of AI-based systems, as well as to examine the role of their learning motivations. As a result, perceived usefulness and perceived ease of use of AI-based systems positively impacted students’ attitude, behavioral intentions, and their final, actual use of AI-based systems, while college students’ attitude towards AI-based systems showed an insignificant impact on students’ learning motivations of achieving their goals and subjective norms. Collectively, the findings of the present study could enrich the knowledge of the technology acceptance model (TAM) and the application of the TAM to explain students’ behavior in terms of the adoption of AI-based systems.
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