University Students' Attitudes Toward ChatGPT Profiles and Their Relation to ChatGPT Intentions

被引:18
作者
Zhang, Yuchi [1 ,2 ]
Yang, Xianmin [1 ,2 ,4 ]
Tong, Wei [3 ]
机构
[1] Jiangsu Normal Univ, Sch Smart Educ, Dept Educ Technol, Xuzhou, Peoples R China
[2] Jiangsu Normal Univ, Jiangsu Engn Res Ctr Educ Informatizat, Xuzhou, Peoples R China
[3] Shanghai Normal Univ, Sch Psychol, Shanghai, Peoples R China
[4] Jiangsu Normal Univ, Sch Smart Educ, Xuzhou, Jiangsu, Peoples R China
关键词
Attitudes toward ChatGPT profile; person-centered approach; ChatGPT behavioral intentions; ChatGPT; higher education; LATENT CLASS; ARTIFICIAL-INTELLIGENCE; PREDICTIVE-VALIDITY; GENDER-DIFFERENCES; ACCEPTANCE; BEHAVIOR; ITEM;
D O I
10.1080/10447318.2024.2331882
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
ChatGPT, a cutting-edge artificial intelligence (AI) tool with the potential to transform education, has gained global recognition. Learners' attitudes toward new technologies significantly influence their use of AI tools, such as ChatGPT. However, variable-centered studies struggle to fully capture potential heterogeneity attitudes. This study employed a person-centered approach (latent profile analysis) and thematic analysis to uncover students' attitudes and behavioral intentions regarding ChatGPT. Utilizing a meticulous stratified random sampling approach, this study conducted a mixed-method study based on representative data from 850 Chinese university students, revealing three profiles: Positive Embracers, Cautious Rational Optimism, and Complex Attitudinal Profile. Of the participants, 80.2% showed Cautious Rational Optimism profile, where Positive Embracers showed notably higher ChatGPT intentions. These findings emphasize the need for multidimensional approaches when studying university students' ChatGPT attitudes. This study is the first to explore and uncover attitude diversity, offering new directions and strong evidence for future research and education.
引用
收藏
页码:3199 / 3212
页数:14
相关论文
共 63 条
[61]  
Wardat Y., 2023, EURASIA J MATH SCI T, V19, DOI DOI 10.29333/EJMSTE/13272
[62]   Generative Artificial Intelligence Acceptance Scale: A Validity and Reliability Study [J].
Yilmaz, Fatma Gizem Karaoglan ;
Yilmaz, Ramazan ;
Ceylan, Mehmet .
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2024, 40 (24) :8703-8715
[63]   Using Latent Profile Analysis to Identify Associations Between Gestational Chemical Mixtures and Child Neurodevelopment [J].
Yonkman, Amanda M. ;
Alampi, Joshua D. ;
Kaida, Angela ;
Allen, Ryan W. ;
Chen, Aimin ;
Lanphear, Bruce P. ;
Braun, Joseph M. ;
Muckle, Gina ;
Arbuckle, Tye E. ;
McCandless, Lawrence C. .
EPIDEMIOLOGY, 2023, 34 (01) :45-55