面向智慧教育的教学大数据实践框架构建与趋势分析
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摘要
随着国内智慧教育实践探索的推进,教育大数据在推动教育创新发展与科学变革上的核心价值逐步凸显。文章从学校导入教育大数据项目、教学大数据的建设与应用以及数据驱动的精准教学范式四个方面构建了教学大数据的实践框架,提出了国内教学大数据发展的六大趋势:数据贯通教学全流程,助力教师教学活动的精准化设计与实施;全维度、多模态教学数据的采集与分析成为学习分析技术的重点关注方向;各级教育管理者与教师的数据意识逐步增强,数据素养教育日益受到重视;教育大数据项目率先在区、校两个层面落地探索,企业成为核心参与者;大数据与教学实践的融合价值开始显现,公众认知度逐步提升;智慧课堂与学业测评作为大数据应用的先导区和热点区,将受到政府、企业、学校以及家长的更多关注。文章最后分析了国内教学大数据发展面临的五大现实挑战,即教师数据处理能力不足、线下学习数据采集困难、校企合作机制与规约机制不清晰、教育大数据产品独立运行、数据分析模型的科学性及准确性有待提升,并提出相关发展建议,期望对我国教学大数据的建设与应用提供一定指导。
With the advancement of smart education in China, the core value of educational big data in promoting the development of educational innovation and scientific reform has gradually become prominent. The article constructs a practical framework of educational big data from three aspects of the introduction of educational big data projects, the construction and application of educational big data, and the data-driven precision teaching paradigm, and then proposes six major trends in the development of domestic educational big data: data will go through the entire process of teaching and assist the accurate design and implementation of teachers' teaching activities; the acquisition and analysis of all-dimensional and multimodal teaching data will become the focus of learning analysis technology; educational administrators and teachers at all levels will gradually increase their data awareness and data literacy education will receive increasing attention; the educational big data projects will be carried out in the district and schools initiatively and the company will become a core participant; the value of integration of big data and teaching practice begins to show, and public awareness will gradually increase; smart classrooms and academic assessment are the leading areas and hotspots for big data application and they will attract more attention from the government, companies, schools and parents. Finally, the article analyzes five major challenges faced by the development of domestic educational big data: insufficient data processing ability of teachers, the difficult acquisition of offline learning data, unclear school-enterprise cooperation mechanism and statutory mechanism, independent running of educational big data products,and the improvement of the scientific and accurate data analysis model. Then, this article puts forward some developmental suggestions for the construction and application of educational big data in China.
With the advancement of smart education in China, the core value of educational big data in promoting the development of educational innovation and scientific reform has gradually become prominent. The article constructs a practical framework of educational big data from three aspects of the introduction of educational big data projects, the construction and application of educational big data, and the data-driven precision teaching paradigm, and then proposes six major trends in the development of domestic educational big data: data will go through the entire process of teaching and assist the accurate design and implementation of teachers' teaching activities; the acquisition and analysis of all-dimensional and multimodal teaching data will become the focus of learning analysis technology; educational administrators and teachers at all levels will gradually increase their data awareness and data literacy education will receive increasing attention; the educational big data projects will be carried out in the district and schools initiatively and the company will become a core participant; the value of integration of big data and teaching practice begins to show, and public awareness will gradually increase; smart classrooms and academic assessment are the leading areas and hotspots for big data application and they will attract more attention from the government, companies, schools and parents. Finally, the article analyzes five major challenges faced by the development of domestic educational big data: insufficient data processing ability of teachers, the difficult acquisition of offline learning data, unclear school-enterprise cooperation mechanism and statutory mechanism, independent running of educational big data products,and the improvement of the scientific and accurate data analysis model. Then, this article puts forward some developmental suggestions for the construction and application of educational big data in China.
引文
[1]陈琳,孙梦梦,刘雪飞.智慧教育渊源论[J].电化教育研究,2017(2):13-18.
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[3]杨现民,王榴卉,唐斯斯.教育大数据的应用模式与政策建议[J].电化教育研究,2015(9):54-61,69.
[4]杨现民,骆娇娇,刘雅馨,陈世超.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,2017,38(12):13-20,26.
[5]孙众,蘧征,杨现民,骆力明.有意义的大数据与教学优化改革[J].电化教育研究,2018(3):43-48,61.
[6]杨现民,李新,田雪松.学校导入教育大数据项目:动因、模式、路径与误区[J].中国电化教育,2018(1):50-58.
[7]孙曙辉,刘邦奇.基于动态学习数据分析的智慧课堂模式[J].中国教育信息化,2015(22):21-24.
[8]钟启泉.基于核心素养的课程发展:挑战与课题[J].全球教育展望,2016(1):3-25.
[9]姜强,赵蔚,李松,王朋娇.个性化自适应学习研究——大数据时代数字化学习的新常态[J].中国电化教育,2016(2):25-32.
[10]穆肃,左萍萍.信息化教学环境下课堂教学行为分析方法的研究[J].电化教育研究,2015(9):62-69.
[11]刘邦奇.“互联网+”时代智慧课堂教学设计与实施策略研究[J].中国电化教育,2016(10):51-56,73.
[12] BLIKSTEIN P, WORSLEY M. Multimodal learning analytics and education data mining:using computational technologies to measure complex learning tasks[J]. Journal of learning analytics,2016(2):220-238.
[2]杨现民,余胜泉.智慧教育体系架构与关键支撑技术[J].中国电化教育,2015(1):77-84.
[3]杨现民,王榴卉,唐斯斯.教育大数据的应用模式与政策建议[J].电化教育研究,2015(9):54-61,69.
[4]杨现民,骆娇娇,刘雅馨,陈世超.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,2017,38(12):13-20,26.
[5]孙众,蘧征,杨现民,骆力明.有意义的大数据与教学优化改革[J].电化教育研究,2018(3):43-48,61.
[6]杨现民,李新,田雪松.学校导入教育大数据项目:动因、模式、路径与误区[J].中国电化教育,2018(1):50-58.
[7]孙曙辉,刘邦奇.基于动态学习数据分析的智慧课堂模式[J].中国教育信息化,2015(22):21-24.
[8]钟启泉.基于核心素养的课程发展:挑战与课题[J].全球教育展望,2016(1):3-25.
[9]姜强,赵蔚,李松,王朋娇.个性化自适应学习研究——大数据时代数字化学习的新常态[J].中国电化教育,2016(2):25-32.
[10]穆肃,左萍萍.信息化教学环境下课堂教学行为分析方法的研究[J].电化教育研究,2015(9):62-69.
[11]刘邦奇.“互联网+”时代智慧课堂教学设计与实施策略研究[J].中国电化教育,2016(10):51-56,73.
[12] BLIKSTEIN P, WORSLEY M. Multimodal learning analytics and education data mining:using computational technologies to measure complex learning tasks[J]. Journal of learning analytics,2016(2):220-238.