29,825 | 455 | 264 |
下载次数 | 被引频次 | 阅读次数 |
新技术浪潮汹涌而至。大数据、并行计算和深度学习驱动人工智能技术飞速发展,并重塑教育新形态。人工智能教育应用现状与发展趋势研究有助于推动技术与教育的深度融合发展。该文从技术发展的角度回顾了人工智能的发展历程,概述了人工智能发展史上的三次浪潮,揭示了人工智能的三大要素与驱动力,阐述了人工智能在教育领域中的四大具体应用形态,分析了人工智能教育应用的五大典型特征,并指出其未来的发展趋势,最后归纳并构建了人工智能与教育的融合创新发展体系,旨在为我国人工智能与教育的融合发展提供理论指导。
Abstract:The new wave of technology is surging. Big data, parallel computing and deep learning drive the rapid development of artificial intelligence, and reshape the new paradigm of education. Research on the application status and development trends of artificial intelligence in education helps to promote the deep integration of technology and education. This paper reviews the development of artificial intelligence from the perspective of technology, outlines the iconic development of the research methods in the three waves of artificial intelligence, and reveals the three internal factors and external driving force of artificial intelligence. Then it elaborates the four specific application forms of artificial intelligence technology in education, analyzes the five typical characteristics of the application of artificial intelligence in education, and points out its future development trends. Finally, it constructs the architecture of integrational and innovational system of artificial intelligence and education based on above research, which aims at providing theoretical guidance for the development of artificial intelligence and education in China.
[1]贾积有.国外人工智能教育应用最新热点问题探讨[J].中国电化教育,2010,(7):113-118.
[2]闫志明,唐夏夏,秦旋等.教育人工智能(EAI)的内涵、关键技术与应用趋势——美国《为人工智能的未来做好准备》和《国家人工智能研发战略规划》报告解析[J].远程教育杂志,2017,35(1):26-35.
[3]余明华,冯翔,祝智庭.人工智能视域下机器学习的教育应用与创新探索[J].远程教育杂志,2017,35(3):11-21.
[4]唐烨伟,郭丽婷,解月光,钟绍春.基于教育人工智能支持下的STEM跨学科融合模式研究[J].中国电化教育,2017,(8):46-52.
[5]张剑平,张家华.我国人工智能课程实施的问题与对策[J].中国电化教育,2008,(10):95-98.
[6]吴永和,刘博文,马晓玲.构筑“人工智能+教育”的生态系统[J].远程教育杂志,2017,35(5):27-39.
[7]The Electronic Frontier Foundation.Measuring the Progress of AI Research[DB/OL].https://www.eff.org/files/AI-progress-metrics.html#Vision,2017-10-15.
[8]李开复,王咏刚.人工智能[M].北京:文化发展出版社,2017.5-25.
[9]Frank Chen.AI,Deep Learning and Machine Learning:A Primer[DB/OL].http://a16z.com/2016/06/10/ai-deep-learningmachines,2017-10-15.
[10]Hwang G J,Kuo F R,Yin P Y,et al.A Heuristic Algorithm for planning personalized learning paths for context-aware ubiquitous learning[J].Computers&Education,2010,54(2):404-415.
[11]梁迎丽,梁英豪.基于语音评测的英语口语智能导师系统研究[J].现代教育技术,2012,22(11):82-85.
[12]Nkambou R,Mizoguchi R,Bourdeau J.Advances in Intelligent Tutoring Systems[M].Berlin:Springer Heidelberg,2010.
[13]Boumiza S,Bekiarski A,Souilem D,et al.Development of model for automatic tutor in e-learning environment based on student reactions extraction using facial recognition[A].2017 15th International Conference on Electrical Machines,Drives and Power Systems(ELMA)[C].Sofia:IEEE,2017.488-492.
[14]Petrovica S,Anohina-Naumeca A,Ekenel H K.Emotion Recognition in Affective Tutoring Systems:Collection of Ground-truth Data[J].Procedia Computer Science,2017,(104):437-444.
[15]Graesser A C.Conversations with Auto Tutor help students learn[J].International Journal of Artificial Intelligence in Education,2016,26(1):124-132.
[16]许骏,柳泉波.IT技能测评自动化技术[J].小型微型计算机系统,2001,22(12):1489-1493.
[17]Educational Testing Service.Text Evaluator Capability[DB/OL].http://www.ets.org/research/topics/as_nlp/educational_applications/,2017-10-15.
[18]Burstein J.The E-rater scoring engine:Automated essay scoring with natural language processing[A].Mahwah.M.d.shermis&J.c.burstein[C].NJ:Lawrence Erlbaum Associates,2003.113-121.
[19]Chicago museum of science+industry.Code Fred:Survival Mode[DB/OL].http://www.msichicago.org/experiment/games/code-fred-survivalmode/,2017-10-16.
[20]Benitti F B V,Spolavr N.How Have Robots Supported STEM Teaching?[DB/OL].https://www.kukakore.com/robotic-stemeducation/,2017-10-15.
[21]Peng Y X,Zhu W W,Zhao Y,et al.Cross-media analysis and reasoning:advances and directions[J].Frontiers of Information Technology&Electronic Engineering,2017,18(1):44-57.
基本信息:
DOI:
中图分类号:G434
引用信息:
[1]梁迎丽,刘陈.人工智能教育应用的现状分析、典型特征与发展趋势[J].中国电化教育,2018,No.374(03):24-30.
基金信息:
江苏省教育科学“十三五”规划重大课题“教育信息化与教育教学改革研究”(项目编号:A/2016/06);; 江苏高校哲学社会科学研究基金项目“基于大数据的高校智慧学习模型构建与应用研究”(项目编号:2017SJB0088);; 南京邮电大学教育科学“十三五”规划2017年度课题“基于大数据的智慧学习模式研究”(项目编号:GJS-XKT1717)阶段性成果