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University Students’ Usage of Generative Artificial Intelligence for Sustainability: A Cross-Sectional Survey from China

Author

Listed:
  • Lin Xiao

    (Faculty of Educational Studies, Universiti Putra Malaysia, Serdang 43400, Malaysia
    Faculty of Teacher Education, Baise University, Baise 533000, China)

  • How Shwu Pyng

    (Faculty of Educational Studies, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Ahmad Fauzi Mohd Ayub

    (Faculty of Educational Studies, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Zhihui Zhu

    (Faculty of Educational Studies, Universiti Putra Malaysia, Serdang 43400, Malaysia
    Faculty of Teacher Education, Baise University, Baise 533000, China)

  • Jianping Gao

    (Faculty of Educational Studies, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Zehu Qing

    (Faculty of Teacher Education, Baise University, Baise 533000, China)

Abstract

The rapid development of generative artificial intelligence (GenAI) technology has triggered extensive discussions about its potential applications in sustainable higher education. Based on the technology acceptance model (TAM) and task–technology fit (TTF) theory, this research aimed to investigate the current situations and challenges of Chinese university students using GenAI in four typical task scenarios. This was performed using a cross-sectional research design. The data were collected via questionnaire, with 486 undergraduates from a Chinese university participating. The data analysis methods include descriptive statistics, inferential statistics, and content analysis. The results show that more than 70% of university students actively use GenAI, but nearly half of them are not very proficient in its use. Doubao and ERNIE Bot are the GenAI tools they prefer most. The primary functions they use are text production and information retrieval. They mainly learn the relevant knowledge and skills through self-media and knowledge-sharing platforms. Among the four typical task scenarios, GenAI is widely used in course learning and research activities, while its application in daily life and job search is relatively limited. The analysis of demographic variables shows that grade and major have a significant impact on university students’ use of GenAI. In addition, university students suggest that universities should offer relevant courses or lectures and provide comprehensive technical support to improve the popularity and operability of GenAI. This study provides suggestions for universities, education administration departments, and technology development departments to improve GenAI services. It will help universities optimize the allocation of educational resources and promote educational equity for sustainability.

Suggested Citation

  • Lin Xiao & How Shwu Pyng & Ahmad Fauzi Mohd Ayub & Zhihui Zhu & Jianping Gao & Zehu Qing, 2025. "University Students’ Usage of Generative Artificial Intelligence for Sustainability: A Cross-Sectional Survey from China," Sustainability, MDPI, vol. 17(8), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3541-:d:1635126
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    References listed on IDEAS

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    1. Firuz Kamalov & David Santandreu Calonge & Ikhlaas Gurrib, 2023. "New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution," Sustainability, MDPI, vol. 15(16), pages 1-27, August.
    2. Sandra Saúde & João Paulo Barros & Inês Almeida, 2024. "Impacts of Generative Artificial Intelligence in Higher Education: Research Trends and Students’ Perceptions," Social Sciences, MDPI, vol. 13(8), pages 1-19, August.
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