Undergraduate Students’ Voices on Generative AI: Advantages and Challenges in Cultural Industry Management at SFU
Conference proceedings article
Authors/Editors
Strategic Research Themes
Publication Details
Author list: Zhengyi Zhao, You Zhou, Li Hua, Mongkhon Narmluk, Tanatorn Tongsumrith
Publication year: 2025
Title of series: IIARP International Conference Abstract Proceedings Series
Number in series: 6
Volume number: 3
Start page: 22
End page: 27
Number of pages: 6
Languages: English-United States (EN-US)
Abstract
With the rapid advancement of generative artificial intelligence (GenAI), cultural industry education is facing both unprecedented opportunities and challenges. This study investigates the perceptions, application practices, and future expectations of undergraduate students majoring in Cultural Industry Management at Sichuan Film and Television Academy regarding the use of GenAI tools such as ChatGPT and Midjourney. Using a quantitative survey method, data were collected from 300 students across four academic years. The survey focused on three dimensions: perceived benefits of GenAI in learning, practical usage in academic and creative contexts, and expectations for its role in future career development.Findings indicate a generally positive attitude toward GenAI. Students highly recognized its value in improving learning efficiency, supporting repetitive or complex tasks, and enhancing confidence in academic work. GenAI was widely applied in cultural project planning, creative content production, and brainstorming, while its role in formal academic writing received more cautious feedback. Students also expressed strong anticipation for the integration of GenAI-related training into their curriculum, reflecting a perceived gap between technological development and educational implementation.The study highlights the emerging importance of AI literacy as a foundational competency in cultural industry education. It suggests that universities should actively respond to students’ needs by incorporating AI education into general and professional training, emphasizing both technical skills and ethical awareness. While the study provides meaningful information, future research should incorporate qualitative methods to capture deeper insights and expand sample diversity across institutions.
Keywords
Generative AI, Student perception, undergraduate education






