Analysis of Differences in AI Usage across Academic Disciplines and Their Causes: Taking DeepSeek as an Example

DOI: https://doi.org/10.62517/jhet.202615201

Author(s)

Minjing Li, Lulu Mei, Junxi Shi, Xin Xie, Jie Dong

Affiliation(s)

School of Economics, Management and Law, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi, China

Abstract

The widespread adoption of generative AI is reshaping the way college students learn, and the relationship between AI and college students has sparked increasing discussion. However, there has been a lack of in-depth research into whether there are significant differences in how students from different disciplinary backgrounds utilize these tools. Based on in-depth interviews with 60 junior and senior students from science and engineering, humanities and social sciences, and applied social sciences disciplines at universities in Jiangxi, this paper examines disciplinary differences in the use of AI tools such as DeepSeek and explores the reasons behind these differences in usage behavior shaped by disciplinary contexts from multiple perspectives. The study found that different disciplines possess unique ways of thinking and underlying logic, and students’ priorities when using DeepSeek also vary. Through summarization and analysis, this paper proposes discipline-specific teaching strategies and advocates for students to develop a discipline-oriented awareness of usage, providing a reference for AI education in higher education.

Keywords

Disciplinary Context; Generative AI; Deepseek; Disciplinary Differences

References

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