Unveiling the Mechanisms of the Development of Students' Artificial Intelligence Application Abilities in Interdisciplinary Education

IF 2 3区工程技术 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Applications in Engineering Education Pub Date : 2025-05-04 DOI:10.1002/cae.70046

Zhizhong Xing, Zhijun Meng, Xin Zhang, Li Tan, Lin Yang, Xiaojun Guo, Huidong Wu

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引用次数: 0

Abstract

The convergence of multiple disciplines like medicine and engineering has spurred the swift progress of technologies including big data and artificial intelligence in the educational realm. The sustainable development of students' artificial intelligence application abilities is an important task in education. To enhance the precision and interdisciplinary nature of research in improving students' artificial intelligence application abilities, our study delves deeply into the mechanisms behind these abilities. We innovatively used cutting-edge methods such as knowledge graphs to conduct multidimensional analysis, combined with the background of the times to explore the reasons for the changes in research hotspots and publication volume, and comprehensively presented the research process and development status of students' artificial intelligence application abilities from a global perspective. We found that the field of students' artificial intelligence application abilities is gradually shifting towards interdisciplinary integration with strong comprehensiveness, and deep cooperation across countries, disciplines, and teams will bring greater and more profound development opportunities. On the path of interdisciplinary intersection and artificial intelligence integration, this study provides references and new insights into the development trends of students' artificial intelligence application abilities. Additionally, it effectively promotes the scientific development of students' abilities in the field of artificial intelligence applications at the intersection of multiple disciplines such as medicine and engineering.

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揭示跨学科教育中学生人工智能应用能力发展的机制

医学和工程学等多学科的融合，推动了教育领域大数据、人工智能等技术的快速发展。学生人工智能应用能力的可持续发展是教育中的一项重要任务。为了提高研究在提高学生人工智能应用能力方面的精确性和跨学科性质，我们的研究深入探讨了这些能力背后的机制。我们创新性地运用知识图谱等前沿方法进行多维度分析，结合时代背景，探究研究热点和发表量变化的原因，从全球视角全面呈现学生人工智能应用能力的研究过程和发展现状。我们发现，学生人工智能应用能力领域正逐步向综合性强的跨学科融合方向转变，跨国家、跨学科、跨团队的深度合作将带来更大、更深刻的发展机遇。本研究在跨学科交叉、人工智能融合的道路上，为学生人工智能应用能力的发展趋势提供了参考和新的见解。此外，它有效地促进了学生在医学和工程等多学科交叉的人工智能应用领域能力的科学发展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Applications in Engineering Education 工程技术-工程：综合

CiteScore

7.20

自引率

10.30%

发文量

100

审稿时长

6-12 weeks

期刊介绍： Computer Applications in Engineering Education provides a forum for publishing peer-reviewed timely information on the innovative uses of computers, Internet, and software tools in engineering education. Besides new courses and software tools, the CAE journal covers areas that support the integration of technology-based modules in the engineering curriculum and promotes discussion of the assessment and dissemination issues associated with these new implementation methods.