教育人工智能的发展态势与未来发展机制
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摘要
教育人工智能承载着教育和社会的深切期望,文章从其两大发展目标——构建智能自适应学习环境、揭示学习发生原理与机制入手,剖析了教育人工智能的发展现状:首先,人工智能已经逐步渗透到"教、学、考、评、管、治"等系统层面。其次,人工智能已经成为助推教学变革的"利器"之一,深刻影响着学情分析、教学策略制定、教学资源选择、教学过程实施、教学评价与管理等具体教学环节,彰显了人工智能应用于教学实践的精准化、适切化、智能化、协同化、多元化和全面化等特点及优势。最后,文章认为教育人工智能应从思想、应用、推广和合作四个方面建立未来发展机制。
Educational Artificial Intelligence(EAI) carries deep expectations from education and society. Starting from the two development goals of EAI included building an intelligent adaptive learning environment and revealing the principles and mechanisms of learning, this paper analyzed the current development situation of EAI. Firstly, artificial intelligence has gradually penetrated into the system levels of "teaching, learning, examination, evaluation, management and governance". Secondly, artificial intelligence has become one of the "tools" to promote teaching reform, profoundly affecting the specific teaching links of learning situation analysis, teaching strategy formulation, teaching resource selection, teaching process implementation, teaching evaluation and management, and showing the characteristics and advantages of precision, appropriateness, intelligence, cooperation, diversification and comprehensiveness in the application of artificial intelligence in teaching practice. Finally, this paper suggested that EAI should establish future development mechanism from four aspects of thought, application, promotion and cooperation.
Educational Artificial Intelligence(EAI) carries deep expectations from education and society. Starting from the two development goals of EAI included building an intelligent adaptive learning environment and revealing the principles and mechanisms of learning, this paper analyzed the current development situation of EAI. Firstly, artificial intelligence has gradually penetrated into the system levels of "teaching, learning, examination, evaluation, management and governance". Secondly, artificial intelligence has become one of the "tools" to promote teaching reform, profoundly affecting the specific teaching links of learning situation analysis, teaching strategy formulation, teaching resource selection, teaching process implementation, teaching evaluation and management, and showing the characteristics and advantages of precision, appropriateness, intelligence, cooperation, diversification and comprehensiveness in the application of artificial intelligence in teaching practice. Finally, this paper suggested that EAI should establish future development mechanism from four aspects of thought, application, promotion and cooperation.
引文
[1]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,(1):26-35.
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[5]唐烨伟,郭丽婷,解月光,等.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.
[6]McGraw-Hill Education.What is LearnSmart?[OL].
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[9][17]吴晓如,王政.人工智能教育应用的发展趋势与实践案例[J].现代教育技术,2018,(2):5-11.
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[12]雷云鹤,祝智庭.基于预学习数据分析的精准教学决策[J].中国电化教育,2016,(6):27-35.
[13]李昕,荆永君,王鹏.智能授导系统中的教学策略研究[J].中国电化教育,2012,(10):126-130.
[14]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,(3):24-30.
[15]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,(2):404-415.
[16]杨现民,骆娇娇,刘雅馨,等.数据驱动教学:大数据时代教学范式的新走向[J].电化教育研究,2017,(12):13-20、26.
[18]李保强,吴笛.基于知识关联的学习资源混合协同过滤推荐研究[J].电化教育研究,2016,(6):77-83.
[19]Bauman K,Tuzhilin A.Recommending remedial learning materials to students by filling their knowledge gaps[J].MIS Quarterly.2018,(1):313-332.
[20]牟智佳.学习者数据肖像支撑下的个性化学习路径破解--学习计算的价值赋予[J].远程教育杂志,2016,(6):11-19.
[21]陈晓珊.人工智能时代重新反思教育的本质[J].现代教育技术,2018,(1):31-37.
[2]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,(5):27-39.
[3]Luckin R,Holmes W,Grifths M,et al.Intelligence unleashed:An argument for AI in education[R].London:Pearson,2016:18-21.
[4]姜强,赵蔚,李松,等.大数据背景下的精准个性化学习路径挖掘研究--基于AprioriAll的群体行为分析[J].电化教育研究,2018,(2):45-52.
[5]唐烨伟,郭丽婷,解月光,等.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.
[6]McGraw-Hill Education.What is LearnSmart?[OL].
[7]Knewton.Updated instructor experience[OL].
[8]王帆.从智慧教育视角论教育数据的变迁与潜能[J].中国电化教育,2015,(8):10-15.
[9][17]吴晓如,王政.人工智能教育应用的发展趋势与实践案例[J].现代教育技术,2018,(2):5-11.
[10]智慧教育宣言.首届智慧教育国际研讨会会议成果[J].现代远程教育研究,2017,(6):102.
[11]Lonn S,Krumm A E,Waddington R J,et al.Bridging the gap from knowledge to action:Putting analytics in the hands of academic advisors[A].International conference on learning analytics and knowledge[C].ACM,2012:184-187.
[12]雷云鹤,祝智庭.基于预学习数据分析的精准教学决策[J].中国电化教育,2016,(6):27-35.
[13]李昕,荆永君,王鹏.智能授导系统中的教学策略研究[J].中国电化教育,2012,(10):126-130.
[14]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,(3):24-30.
[15]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,(2):404-415.
[16]杨现民,骆娇娇,刘雅馨,等.数据驱动教学:大数据时代教学范式的新走向[J].电化教育研究,2017,(12):13-20、26.
[18]李保强,吴笛.基于知识关联的学习资源混合协同过滤推荐研究[J].电化教育研究,2016,(6):77-83.
[19]Bauman K,Tuzhilin A.Recommending remedial learning materials to students by filling their knowledge gaps[J].MIS Quarterly.2018,(1):313-332.
[20]牟智佳.学习者数据肖像支撑下的个性化学习路径破解--学习计算的价值赋予[J].远程教育杂志,2016,(6):11-19.
[21]陈晓珊.人工智能时代重新反思教育的本质[J].现代教育技术,2018,(1):31-37.