A Study of Undergraduates’ Behavioral Intention to Use Generative AI Tools—Ernie Bot as An Example
DOI:
https://doi.org/10.54097/9xw63p10Keywords:
GenAI; UTAUT; Behavioral Intention; Ernie Bot.Abstract
With the rapid advancement of artificial intelligence technology, its influence on various sectors is increasing. Ernie Bot, a leading tool in generative AI, has garnered significant attention and application. This study utilizes the Unified Theory of Acceptance and Use of Technology (UTAUT) and introduces the concepts of Perceived Risk and Information Quality to construct a model that examines the factors influencing undergraduates’ behavioral intention to use generative AI tools like Ernie Bot. Using questionnaire data collected from 175 undergraduates, a structural equation model was employed to analyze the relationships between variables. The findings indicate that Social Influence, Information Quality, and Performance Expectancy positively impact the Behavioral Intention to use Ernie Bot. However, Effort Expectancy was not found to be a significant determinant of Behavioral Intention among undergraduates. Additionally, the study revealed that Perceived Risk did not negatively affect Behavioral Intention. These results offer valuable insights for the design and development of generative AI products, suggesting that enhancing Information Quality and leveraging Social Influence could improve user acceptance.
Downloads
References
[1] Chan, Cecilia Ka Yuk, and Hu Wenjie. Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 2023, 20(1). https://doi.org/10.1186/s41239-023-00411-8
[2] Ruiz-Rojas, Lena Ivannova, Luis Salvador-Ullauri, and Patricia Acosta-Vargas. Collaborative working and critical Thinking: adoption of generative artificial intelligence tools in higher education. Sustainability, 2024, 16(13), 5367. https://doi.org/10.3390/su16135367
[3] Mowreader, A. (2024, June 28). One-third of college instructors are using genAI—here’s how. Inside Higher Education News, Events and Jobs. https://www.insidehighered.com/news/student-success/academic-life/2024/06/28/one-third-college-instructors-are-using-genai-heres
[4] Dai Bingfang and Chen Guiping. Research on dialogue and Improvement Strategy of Artificial Intelligence question answering System--taking Ernie Bot as an example. Computer Knowledge and Technology, 2024, (08),14-16+38.doi: 10.14004/j.cnki.ckt.2024.0364.
[5] Zhu Lingkui and Zhang Feng. Application of artificial intelligence knowledge enhanced large language model Ernie Bot in hospital pharmacy practice. Health Protection and Promotion, 2023, (18), 1430-1436.
[6] Sun Leng. Midea Group access Baidu Ernie Bot smart home human-computer dialogue ability to upgrade. Home Appliance, 2023, (3), 74-74.
[7] Venkatesh, Viswanath, Michael G. Morris, Gordon B. Davis, and Fred D. Davis. User acceptance of information technology: Toward a unified view. MIS quarterly, 2003: 425-478.
[8] Chen, Junxun, Tao Wang, Zhenyu Fang, and Hongtao Wang. Research on elderly users' intentions to accept wearable devices based on the improved UTAUT model. Frontiers in Public Health, 2023, 10: 1035398.
[9] Al Darayseh, Abdulla. Acceptance of artificial intelligence in teaching science: Science teachers' perspective. Computers and Education: Artificial Intelligence, 2023, 4: 100132.
[10] Abbas, Sammar, Alhamzah Alnoor, Teh Sin Yin, Abdullah Mohammed Sadaa, Yousif Raad Muhsen, Khai Wah Khaw, and Yuvaraj Ganesan. Antecedents of trustworthiness of social commerce platforms: A case of rural communities using multi group SEM & MCDM methods. Electronic Commerce Research and Applications, 2023, 62, 101322. https://doi.org/10.1016/j.elerap.
[11] Strzelecki, Artur. To use or not to use ChatGPT in higher education? A study of students’ acceptance and use of technology. Interactive Learning Environments, 2023, 1–14. https://doi.org/10.1080/10494820.2023.2209881
[12] Moorthy, Krishna, Loh Chun T'ing, Kiing Siew Ming, Chiong Chui Ping, Ler Yu Ping, Lim Qiao Joe, and Wong Ying Jie. "Behavioral intention to adopt digital library by the undergraduates." International Information & Library Review, 2019, 51 (2): 128-144.
[13] Lai, Chung Yee, Kwok Yip Cheung, Chee Seng Chan, and Kuok Kei Law. Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students. Computers and Education: Artificial Intelligence, 2024, 6: 100246.
[14] Shao Pinglin. Young people are cautiously optimistic about generative AI. China Economic Herald, 2024, 003. doi: 10.28095/n.cnki.ncjjd.2024.000663.
[15] Aryani, Dwi Nita, Padmalini Singh, Yun Xuan Khor, Daisy Mui Hung Kee, Kornelia Selvia, Cui Wen Lee, Yee Hsien Lee, and Levisha Anantharavoo. Factors influencing consumer behavioral intention to use food delivery services: a study of Foodpanda. Journal of the Community Development in Asia/Journal of the Community Development in Asia, 2022, 5(1), 69–79. https://doi.org/10.32535/jcda.v5i1.1386
[16] Tan, Christine Nya-Ling, Mcxin Tee, and Kian Yeik Koay. Discovering students’ continuous intentions to use ChatGPT in higher education: a tale of two theories. Asian Education and Development Studies. 2024. https://doi.org/10.1108/aeds-04-2024-0096
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
