[1]吴永和,李彤彤.机器智能视域下的机器人教育发展现状、实践、反思与展望[J].远程教育杂志,2018,(04):079-87.[doi:10.15881/j.cnki.cn33-1304/g4.2018.04.010]
 Wu Yonghe,Li Tongtong.The Status, Practice,Reflection and Prospect of Robot Education from the Perspective of Machine Intelligence[J].Distance Education Journal,2018,(04):079-87.[doi:10.15881/j.cnki.cn33-1304/g4.2018.04.010]
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机器智能视域下的机器人教育发展现状、实践、反思与展望()
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《远程教育杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2018年04期
页码:
079-87
栏目:
学术视点
出版日期:
2018-07-12

文章信息/Info

Title:
The Status, Practice,Reflection and Prospect of Robot Education from the Perspective of Machine Intelligence
作者:
吴永和; 李彤彤
华东师范大学 教育学部 教育信息技术学系,上海 200062
Author(s):
Wu Yonghe; Li Tongtong
Department of Education Information Technology, Faculty of Education, East China Normal University, Shanghai 200062
关键词:
机器人机器智能机器人教育创客教育教育机器人人工智能教学设计机器人竞赛
Keywords:
Robot Machine Intelligence Robot Education Maker Education Educational Robot Artificial Intelligence Instructional Design Robotics Competitions
分类号:
G420
DOI:
10.15881/j.cnki.cn33-1304/g4.2018.04.010
文献标志码:
A
摘要:
2018年3月1日,美国在发布的《美国机器智能国家战略》中提到,机器智能可以融入课堂教学,为学生提供个性化的学习体验,并提升教师的教学效率与学生的学习体验。随着教育机器人的出现、创客教育的发展和STEAM教育的需求,机器人教育逐渐走入大众的视野。机器人教育的应用包括教育机器人产品、机器人教材、机器人竞赛与机器人教学活动,而相关学术研究主要集中在目的、技术与方法三个方面。从深度学习、研究体验、生涯指导三个维度设计的教学实践活动表明,机器人教育可以帮助学生学习多学科知识,培养学生的问题解决能力。未来的机器教育将朝学科融合的方向发展,推进机器人教育评价研究与师资培养,并加强“产政学”合作。
Abstract:
The National Machine Intelligence Strategy for the United States issued on March 1, 2018 clearly stated that machine intelligence can be integrated into classroom teaching, providing students with a personalized learning experience, and improving teachers’ teaching efficiency and students’ learning experience. With the advent of educational robots, popularization of maker education and demand for STEAM education, robot education has gradually entered the public’s vision. The applications of robot education include educational robot products, robotics teaching materials, robotics competitions and robot teaching activities. Related academic research focuses on three aspects: educational purpose, key technology and teaching method. The teaching practice designed from three dimensions (deep study, research experience and career guidance) shows that robot education can help students learn multidisciplinary knowledge and develop problem-solving skills. In the future, robot education will carry forward the integration of disciplines. The evaluation of robotics education and robotic teacher training will be promoted, and the cooperation of industry, government and school will be strengthened.

相似文献/References:

[1]陈蕙若,姚中瑞,钟琳,等.引领学习的改变——AECT2017年会评述与思考[J].远程教育杂志,2018,(01):003.[doi:10.15881/j.cnki.cn33-1304/g4.2018.01.001]
 Chen Huiruo,Yao Zhongrui,Zhong Lin,et al.Leading Learning for Change: Commenting and Reflecting on AECT 2017 International Convention[J].Distance Education Journal,2018,(04):003.[doi:10.15881/j.cnki.cn33-1304/g4.2018.01.001]
[2]陈松云,何高大.机器智能视域下的教育发展与实践范式新探——2018《美国机器智能国家战略》的启示[J].远程教育杂志,2018,(03):034.[doi:10.15881/j.cnki.cn33-1304/g4.2018.03.004]
 Chen Songyun,He Gaoda.New Exploration of Educational Development and Practice Paradigm from the Perspective of Machine Intelligence:Inspirations on 2018 A National Machine Intelligence Strategy for the United States[J].Distance Education Journal,2018,(04):034.[doi:10.15881/j.cnki.cn33-1304/g4.2018.03.004]

备注/Memo

备注/Memo:
基金项目:本文系上海市浦江人才计划项目“基于教育大数据的学习分析教育应用创新研究”(项目号:14PJC034)与2016年度教育部-中国移动科研基金项目《国家教育大数据相关问题研究》子课题“教育大数据标准体系研究”(项目号:MCM20160401)的研究成果。
更新日期/Last Update: 1900-01-01