学习者是否愿意使用 ChatGPT?采用先进的两阶段 SEM-神经网络方法预测 ChatGPT 采用的影响因素

IF 3.5 Q1 EDUCATION & EDUCATIONAL RESEARCH
Nattaporn Thongsri, O. Tripak, Yukun Bao
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引用次数: 0

摘要

目的本研究旨在通过对行为科学领域的变量进行理论综合,研究影响学习者接受聊天生成式预培训转换器(ChatGPT)的变量。本研究采用分层随机抽样的方法,从 679 名本科生中收集了数据。采用结构方程建模(SEM)-神经网络两阶段方法对数据进行分析,其中结构方程建模用于研究影响使用 ChatGPT 意向的因素。结果两阶段的 SEM-神经网络方法得出了稳健一致的分析结果,表明变量 "系统质量 (SYQ) "的影响最大,其次是 "认知需求 (CN)"、"信息质量 (INQ)"、"社交需求 (SN)" 和 "情感需求 (AN)",影响程度依次递减。实际意义将行为变量与 IS 变量整合后得出的结果将为教育部、大学和教育工作者等各种组织在学习中应用人工智能技术提供指导。他们应优先考虑系统的质量和支持使用 ChatGPT 学习的技术基础设施。此外,他们还应让学习者做好各方面的准备,包括知识、情感和社会方面。原创性/价值这项研究提出了在学习中实施人工智能技术的挑战,教育机构必须接受这些挑战,以跟上全球技术发展趋势。教育部门应从一开始就将人工智能融入课程规划、教学方法和学习者评估过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Do learners exhibit a willingness to use ChatGPT? An advanced two-stage SEM-neural network approach for forecasting factors influencing ChatGPT adoption
Purpose This study aims to examine the variables that influence learners’ acceptance of chat generative pre-trained transformer (ChatGPT) through the theoretical synthesis of variables in the field of behavioral science. It uses the use and gratifications theory in conjunction with variables related to the information system (IS), as proposed by the Delone and McLean IS success model. Design/methodology/approach This quantitative research collected data from 679 undergraduate students using stratified random sampling. A two-staged structural equation modeling (SEM)-neural network approach was used to analyze the data, with SEM used to study the factors influencing the intention to use ChatGPT. Additionally, an artificial neural network approach was used to confirm the results obtained through SEM. Findings The two-staged SEM-neural network approach yielded robust and consistent analysis results, indicating that the variable “System quality (SYQ)” has the highest influence, followed by “Cognitive need (CN),” “Information Quality (INQ),” “Social need (SN)” and “Affective need (AN)” in descending order of importance. Practical implications The results obtained from integrating the behavioral variables with IS variables will provide guidance to various organizations, such as the Ministry of Education, universities and educators, in the application of artificial intelligence technology in learning. They should prioritize the quality aspect of the system and the technological infrastructure that supports the use of ChatGPT for learning. Additionally, they should prepare learners to be ready in various dimensions, including knowledge, emotions and social aspects. Originality/value This study presents challenges in implementing artificial intelligence technology in learning, which educational institutions must embrace to keep up with the global technological trends. The educational sector should integrate artificial intelligence into the curriculum planning, teaching methods and learner assessment processes from the outset.
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来源期刊
Interactive Technology and Smart Education
Interactive Technology and Smart Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
12.00
自引率
2.30%
发文量
30
期刊介绍: Interactive Technology and Smart Education (ITSE) is a multi-disciplinary, peer-reviewed journal, which provides a distinct forum to specially promote innovation and participative research approaches. The following terms are defined, as used in the context of this journal: -Interactive Technology refers to all forms of digital technology, as described above, emphasizing innovation and human-/user-centred approaches. -Smart Education "SMART" is used as an acronym that refers to interactive technology that offers a more flexible and tailored approach to meet diverse individual requirements by being “Sensitive, Manageable, Adaptable, Responsive and Timely” to educators’ pedagogical strategies and learners’ educational and social needs’. -Articles are invited that explore innovative use of educational technologies that advance interactive technology in general and its applications in education in particular. The journal aims to bridge gaps in the field by promoting design research, action research, and continuous evaluation as an integral part of the development cycle of usable solutions/systems.
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