致力于知识迁移的深度学习探究
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摘要
目前,深度学习和知识迁移已成为教育研究领域的热点议题,但关于深度学习与知识迁移之间关系的研究成果很少。为探究致力于知识迁移的深度学习,文章首先从多个角度,分析了互联网对知识迁移的阻隔;接着,文章详细梳理了知识迁移的内在逻辑:学习者必须在联结大脑与信息的基础上,通过理解性学习、激活记忆中的知识、反思与批判性思维、提取与应用知识,最终才能顺利地实现知识迁移;然后,文章阐释了深度学习与知识迁移之间的关系;最后,文章以深度学习与知识迁移之间的指向关系为依据,深刻剖析了致力于知识迁移的深度学习的路径。探究致力于知识迁移的深度学习,可以推动深度学习和知识迁移的进一步融合,并为互联网学习环境下的深度学习研究提供理论参考。
At present, deep learning and knowledge transfer have become hot topics in the field of educational research.However, there were few research achievements about the relationship between deep learning and knowledge transfer.In order to explore the deep learning dedicated to knowledge transfer, this paper first analyzed the Internet's barriers to knowledge transfer from multiple perspectives. Then, the internal logic of knowledge transfer was combed in detail:based on the connection between brain and information, learners could successfully achieve knowledge transfer through comprehensive learning, activating knowledge in memory, reflective and critical thinking, extracting and applying knowledge. Then, the relationship between deep learning and knowledge transfer was explained. Finally, based on the pointing relationship between deep learning and knowledge transfer, the path of deep learning dedicated to knowledge transfer was deeply analyzed. Exploring the deep learning dedicated to knowledge transfer could promote further integration of deep learning and knowledge transfer, and provide theoretical reference for the deep learning research under Internet learning environment.
At present, deep learning and knowledge transfer have become hot topics in the field of educational research.However, there were few research achievements about the relationship between deep learning and knowledge transfer.In order to explore the deep learning dedicated to knowledge transfer, this paper first analyzed the Internet's barriers to knowledge transfer from multiple perspectives. Then, the internal logic of knowledge transfer was combed in detail:based on the connection between brain and information, learners could successfully achieve knowledge transfer through comprehensive learning, activating knowledge in memory, reflective and critical thinking, extracting and applying knowledge. Then, the relationship between deep learning and knowledge transfer was explained. Finally, based on the pointing relationship between deep learning and knowledge transfer, the path of deep learning dedicated to knowledge transfer was deeply analyzed. Exploring the deep learning dedicated to knowledge transfer could promote further integration of deep learning and knowledge transfer, and provide theoretical reference for the deep learning research under Internet learning environment.
引文
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[26]Mayer R E.Instruction based on visualizations[A].Handbook of Research on Learning and Instruction[C].New York:Routledge,2011:427-445.
[27](美)L·W·安德森等著.皮连生译.学习、教学和评估的分类学--布卢姆教育目标分类学(修订版)[M].上海:华东师范大学出版社,2008:27.
[28]孙妍妍,祝智庭.以深度学习培养21世纪技能--美国《为了生活和工作的学习:在21世纪发展可迁移的知识与技能》的启示[J].现代远程教育研究,2018,(3):9-18.
[2][19]康淑敏.基于学科素养培育的深度学习研究[J].教育研究,2016,(7):111-118.
[3](美)爱因斯坦著.许良英,赵中立,张宣三译.爱因斯坦文集(第三卷)[M].北京:商务印书馆,1979:173-174.
[4]谭维智.互联网时代教育的时间逻辑[J].教育研究,2017,(8):12-24.
[5]刘伟,谭维智.网络时代知识教学的价值诉求、目标与变革路径[J].开放教育研究,2018,(6):81-87.
[6](法)安德烈·焦尔当著.杭零译.学习的本质[M].上海:华东师范大学出版社,2015:36.
[7](丹)伊列雷斯著.孙玫璐译.我们如何学习:全视角学习理论[M].北京:教育科学出版社,2014:14.
[8][9][23][29](美)约翰·D·布兰思福特,安·L·布朗,罗德尼·R·科金著.程可拉,孙亚玲,王旭卿译.人是如何学习的:大脑、心理、经验及学校(扩展版)[M].上海:华东师范大学出版,2012:15、49、43、33.
[10](美)戴尔·H.申克著.韦小满等译.学习理论:教育的视角(第三版)[M].南京:江苏教育出版社,2009:202.
[11]吴秀娟,张浩,倪厂清.基于反思的深度学习:内涵与过程[J].电化教育研究,2014,(12):23-28、33.
[12]Salomon G,Perkins D N.Rocky roads to transfer:Rethinking mechanisms of a neglected phenomenon[J].Educational Psychologist,1989,(2):113-142.
[13](美)B·S·布卢姆等著.罗黎辉,丁证霖,石伟平,等译.教育目标分类学(第一分册认知领域)[M].上海:华东师范大学出版社,1986:18-21.
[14]Marton F,S?lj?R.On qualitative difference in learning:Outcome and process[J].British Journal of Educational Psychology,1976,(1):4-11.
[15]Smith T W,Colby S A.Teaching for deep learning[J].The Clearing House:A Journal of Educational Strategies,Issues and Ideas,2007,(5):205-210.
[16]何克抗.深度学习:网络时代学习方式的变革[J].教育研究,2018,(5):111-115.
[17]何玲,黎加厚.促进学生深度学习[J].计算机教与学,2005,(5):29-30.
[18]刘哲雨,郝晓鑫.深度学习的评价模式研究[J].现代教育技术,2017,(4):12-18.
[20]Mayer R E.Should there be a three-strikes rule against pure discovery learning?[J].American Psychologist,2004,(1):14-19.
[21][25](美)Jensen E,Nickelsen L著.温暖译.深度学习的7种有力策略[M].上海:华东师范大学出版社,2009:18、118.
[22]McCarthy M T.Form of feedback effects on verb learning and near-transfer tasks by sixth graders[J].Contemporary Educational Psychology,1995,(2):140-150.
[24]严文蕃,李娜.互联网时代的教学创新与深度学习--美国的经验与启示[J].远程教育杂志,2016,(2):26-31.
[26]Mayer R E.Instruction based on visualizations[A].Handbook of Research on Learning and Instruction[C].New York:Routledge,2011:427-445.
[27](美)L·W·安德森等著.皮连生译.学习、教学和评估的分类学--布卢姆教育目标分类学(修订版)[M].上海:华东师范大学出版社,2008:27.
[28]孙妍妍,祝智庭.以深度学习培养21世纪技能--美国《为了生活和工作的学习:在21世纪发展可迁移的知识与技能》的启示[J].现代远程教育研究,2018,(3):9-18.