摘要
通过科学知识图谱分析方法,对Scopus数据库中近二十年8660篇的国际人工智能教育研究文献进行深入分析,主要聚焦于国际人工智能教育研究的发展态势和知识结构。结果显示:驱动人工智能研究的主要是政策、经济投入与国际合作;而人工智能教育研究的知识结构间的关系主要涉及机器学习/教育、智能导学系统和人类学习/教育,它们在根本上体现了智能主体(人与机器)间的关系,并凸显数字化学徒制的特征。进而启发人工智能教育专业人才培养:一是要重视政策、经济投入和国际合作等外部动因;二是要紧扣智能主体视域下人机关系及其四种主客体结构的核心内容;三是要加强技术伦理教育。此外,还要应对可能的风险。
Through the method of scientific knowledge map analysis, this study has made an in-depth analysis of 8,660 articles on international artificial intelligence education in the Scopus database in the past two decades, focusing on the factors driving research outputs and its inner knowledge structure. The results show that policy, economic input and international cooperation are the core factors driving AI research. Moreover, the relationship between the knowledge structure of artificial intelligence education research mainly involves machine learning/education, intelligent tutoring system and human learning/education. They fundamentally embody the relationship between intelligent subjects(human and machine), and highlight digital chemical apprenticeship characteristics. In terms of developing artificial intelligence education professionals, policies, economic input, and international cooperation are the crucial external factors. Meanwhile, universities have to pay more attention to the human-machine relationship and its core contents from the perspective of intelligent subjects, strengthening technical ethics education, as well as responding to possible risks.
作者
李祥
陈凤
LI Xiang;CHEN Feng(Guizhou Normal University,Guiyang 550025,China)
出处
《黑龙江高教研究》
北大核心
2020年第4期79-86,共8页
Heilongjiang Researches on Higher Education
基金
2019年贵州省高等学校教学内容和课程体系改革项目“‘课程思政’视域下师范专业教学内容改革路径研究”(编号:2019023)的研究成果。
关键词
人工智能教育
知识结构
智能主体
数字化学徒制
专业人才培养
artificial intelligence education
knowledge structure
intelligent subject
digital apprenticeship
professional talents’cultivation