社会影响和信息质量对商科学生使用生成式人工智能的影响

IF 5.3 2区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Ismail Abdi Changalima, David Amani, Ismail Juma Ismail
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引用次数: 0

摘要

尽管生成式人工智能(AI)在教育环境中的应用日益广泛,但其对塑造学生行为的影响的研究仍相对不足。本研究采用 PLS-SEM 方法探讨了社会影响、信息质量和商科学生使用 ChatGPT 的行为意向之间的关系。通过收集 477 名商科学生的数据,研究揭示了社会影响和信息质量对行为意向的显著影响。此外,信息质量加强了社会影响对行为意向的影响。多组分析显示,社会影响和信息质量对行为意向的影响在女性和男性之间存在差异。然而,信息质量的调节作用在他们之间没有显著差异。此外,在所有假设关系中观察到的效应在一年级学生和二年级学生之间也没有显著差异。本研究通过实证验证了所提出的有关使用 ChatGPT 的行为意向模型,并确定了男女生之间以及一年级和二年级学生之间的统计差异,有助于填补现有的知识空白。此外,本研究还为今后的研究提供了潜在的途径,并为有兴趣了解学生参与生成式人工智能的学者、专业人士和政策制定者提供了宝贵的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social influence and information quality on Generative AI use among business students
Despite the increasing utilisation of generative artificial intelligence (AI) in educational settings, its influence on shaping students’ behaviour remains relatively under-researched. This study employs PLS-SEM to explore the relationships between social influence, information quality, and behavioural intentions regarding ChatGPT usage among business students. Drawing from data collected from 477 business students, the study unveils that both social influence and information quality significantly impact behavioural intentions. Moreover, information quality strengthens the influence of social influence on behavioural intentions. The multigroup analysis reveals that the effects of social influence and information quality on behavioural intentions differ between females and males. However, the moderating effect of information quality does not differ significantly between them. Furthermore, the effects observed in all hypothesised relationships do not differ significantly between first-year and second-year students. By empirically validating the proposed model for behavioural intentions regarding ChatGPT usage and identifying statistical differences among males and females, as well as between first-year and second-year students, this study contributes to filling existing knowledge gaps. Furthermore, the study offers potential avenues for future research and serves as a valuable resource for academics, professionals, and policymakers interested in understanding students' engagement with generative AI.
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来源期刊
CiteScore
8.30
自引率
3.40%
发文量
1601
期刊介绍: ACS Applied Nano Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics and biology relevant to applications of nanomaterials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important applications of nanomaterials.
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