深度学习学科演进及其教育启示研究

Xue Wang, Haiyan He, Ping Li, Lei Zhang
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引用次数: 0

摘要

人工智能教育的显著增长与人工智能技术在现代社会的积极应用是一致的。以Web of Science核心馆藏中以“深度学习”为题的文章及其引用为例,分析并可视化了该领域的学科演变和跨学科进展。不同国家的跨学科特征代表了深度学习科学研究和技术发展的不同方向和趋势。遵循人工智能技术的理论和技术发展规律,特别是跨学科的发展规律,人工智能教育改革需要在教育模式和课程内容上都注重跨学科,将研究与教育深度融合,产学研紧密合作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Disciplinary Evolution of Deep Learning and the Educational Revelation
The significant growing popularity of Artificial Intelligence education is coincidence with the aggressive application of AI technology in modern society. Taking articles titled with “deep learning” and their citations from Web of Science core collections as an example, the disciplinary evolution and interdisciplinary progress of this field are analyzed and visualized. The interdisciplinary characteristics of different countries represent different directions and tendencies of scientific research and technique development on deep learning. Following the rule of theoretical and technological development of AI techniques, especially the interdisciplinary, reform of AI education need to focus on interdisciplinary in both education mode and curriculum content, deep integration of research and education, and close cooperation of industry, universities, and research institutes.
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