首页|基于AIDUA框架的生成式人工智能使用意愿研究

基于AIDUA框架的生成式人工智能使用意愿研究

扫码查看
[目的/意义]探究科研人员使用生成式人工智能技术意愿的影响因素,基于此促进生成式人工智能技术在学术研究及高等教育中的应用。[方法/过程]基于认知评估理论和人工智能接受框架(AIDUA),开发并实证检验了生成式人工智能使用意愿的理论模型,通过三阶段对用户使用意愿进行评估,旨在解释用户使用意愿的形成过程。[结果/结论]用户使用生成式人工智能之前,经历了三阶段的决策过程。社会影响、享乐动机和拟人化对绩效期望和努力期望均呈正相关,拟人化是影响绩效期望和努力期望的最强变量,绩效期望和努力期望对消极情绪呈负相关,而享乐动机对消极情绪的影响不显著,消极情绪与用户的使用意愿呈负相关,结果显示在校身份对努力预期和消极情绪之间具有调节作用。
User Willingness to Use Generative Artificial Intelligence Based on AIDUA Framework
[Purpose/Significance]Generative artificial intelligence(AI)technology has been widely used in many fields,and the application of this technology has become popular among researchers.However,there are few studies on the willingness of researchers willingness to accept generative AI.This leads to an insufficient understanding of the psychological mechanism,cognitive process and behavioral pattern of users'acceptance of generative AI,which limits the ability of theoretical innovation and practical exploration in user information behavior.This study focuses on researchers acceptance of generative AI.By studying the evaluation process of ChatGPT by college students,it explores the acceptance behavior of generative AI.At the same time,it verifies the applicability of the AIDUA model in the new context,and introduces the new variable of school identity,which further extends the AIDUA model.[Method/Process]Based on the cognitive assessment theory and the AI acceptance framework(AIDUA),this paper constructs a theoretical model of the intention to use generative artificial intelligence,and develops and empirically tests the theoretical model of the intention to use generative AI.Taking college students as the main research object,based on the maturity scale in authoritative literature at home and abroad,8 variables and 29 observation variables such as social influence,hedonic motivation and anthropomorphism were designed.College students with experience in using generative AI were invited to participate in the questionnaire survey.SPSS26.0 was used to analyze the data from 294 valid questionnaires collected.SmartPLS 3.2.9 was used to construct a structural equation model to test the hypothesis,and the JN method was used to detect the regulatory effect.[Results/Conclusions]The study found that users went through three stages of decision making before using generative AI.The PLS-SEM results show that:1)Social influence,hedonic motivation and anthropomorphism significantly affect performance expectancy and effort expectancy,and anthropomorphism is the strongest variable affecting performance expectancy and effort expectancy.2)Performance expectancy and effort expectancy are significantly negatively correlated with negative emotions,while hedonic motivation has no significant effect on negative emotions.3)Negative emotions are significantly negatively correlated with users'intension to use.4)School identity moderates the relationship between effort expectancy and negative emotions.This study combines anthropomorphic research on college students'acceptance of generative AI,and provides a framework for the acceptance of generative AI.Researchers can use this framework to better study the acceptance of AI.This study has some limitations.In the future,we will focus on the following three aspects:1)to evaluate the users'acceptance of generative AI in different usage scenarios.2)to use samples of other groups to test the applicability of the model,such as civil servants,librarians,researchers and other groups.3)to incorporate variables from other technology acceptance models into the model,such as ease of use and practicality.

generative artificial intelligenceChatGPTpersonificationuser information behaviorwillingness to usedigital literacy

王伟正、乔鸿、李肖俊、王静静

展开 >

山东师范大学图书馆,济南 250358

山东师范大学商学院,济南 250358

齐鲁工业大学(山东省科学院)数字人文研究中心,济南 250014

齐鲁工业大学(山东省科学院)情报研究所,济南 250014

山东大学新闻与传播学院,济南 250100

展开 >

生成式人工智能 ChatGPT 拟人化 用户信息行为 使用意愿 数字素养

国家自然科学基金青年基金

72304169

2024

农业图书情报学报
中国农业科学院农业信息研究所

农业图书情报学报

影响因子:0.48
ISSN:1002-1248
年,卷(期):2024.36(2)
  • 43