互联网视域下深度学习思维影响机制研究——基于信息素养的中介效应检验
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摘要
信息化浪潮下,信息技术与教育的深度融合对学生学习能力提出更高要求。深度学习作为学生胜任21世纪生活与学习必备的能力,已成为各国争相研究的教育议题。深度学习思维被公认为深度学习能力的重要表征。本研究通过访谈及问卷调查,对北京某高校626名硕士生在互联网环境下的深度学习开展实证研究。研究借助SPSS21. 0和Mplus7. 4探究影响网络深度学习的因素及作用机制,并通过结构方程模型分析信息素养在其中发挥的中介效应。研究发现:传统教学环境下的深度学习、信息素养及环境支持是影响在互联网环境下深度学习思维的核心因素。深度学习能够在传统教学环境与互联网环境之间发生有效迁移。信息素养对传统教学环境下的深度学习与互联网环境下的深度学习思维发挥中介效应。本研究的理论贡献在于扩展了深度学习影响机制的适用情境,引入学习迁移理论、关联主义及信息加工理论为深度学习思维的实证研究增添理论解释力,相关研究发现亦为增强网络深度学习提供实践启示。
Under the tide of IT application,the comprehensive deep integration of information technology and education puts forward a higher level of requirements for learners' learning ability. Deep learning has become an essential issue for students to succeed in the 21 st Century. "Deep learning thinking"is recognized as an important characteristic of the "deep learning"ability. Through literature review,theoretical analysis,preliminary interviews and questionnaire surveys,this research conducts an empirical study on 626 graduate students' deep learning in the Internet environment. Those participants are all from a university in Beijing. Among them,there are 180 male students and 446 female students. In addition,there are 203 first-year graduates,198 second-year graduates,and 225 thirdyear graduates,each accounting for 32. 4%,31. 6% and 35. 9% of the total sample,which are basically distributed in equal proportions. This research uses SPSS21. 0 and Mplus7. 4 to explore the factors and mechanisms that influence the graduates' deep learning in the Internet environment,and analyzes the mediating effects of Information Literacy in the structural equation model. The research found that deep learning method in the traditional teaching environment,information literacy and environmental support are the core factors that influence the graduates' deep learning thinking in the Internet environment. Deep learning can effectively migrate from the traditional teaching environment to the Internet environment. Additionally,information literacy plays a mediating role between deep learning in the traditional teaching environment and deep learning thinking in the Internet environment. The theoretical contribution of this research is to expand the applicable context of the deep learning influence mechanism. Meanwhile,this research also introduces the learning transfer theory,connectivism and information processing theory into the theoretical explanation of the"deep learning thinking in the Internet environment"model. The research findings also provide practical inspiration for enhancing the graduates' deep learning in the Internet environment.
Under the tide of IT application,the comprehensive deep integration of information technology and education puts forward a higher level of requirements for learners' learning ability. Deep learning has become an essential issue for students to succeed in the 21 st Century. "Deep learning thinking"is recognized as an important characteristic of the "deep learning"ability. Through literature review,theoretical analysis,preliminary interviews and questionnaire surveys,this research conducts an empirical study on 626 graduate students' deep learning in the Internet environment. Those participants are all from a university in Beijing. Among them,there are 180 male students and 446 female students. In addition,there are 203 first-year graduates,198 second-year graduates,and 225 thirdyear graduates,each accounting for 32. 4%,31. 6% and 35. 9% of the total sample,which are basically distributed in equal proportions. This research uses SPSS21. 0 and Mplus7. 4 to explore the factors and mechanisms that influence the graduates' deep learning in the Internet environment,and analyzes the mediating effects of Information Literacy in the structural equation model. The research found that deep learning method in the traditional teaching environment,information literacy and environmental support are the core factors that influence the graduates' deep learning thinking in the Internet environment. Deep learning can effectively migrate from the traditional teaching environment to the Internet environment. Additionally,information literacy plays a mediating role between deep learning in the traditional teaching environment and deep learning thinking in the Internet environment. The theoretical contribution of this research is to expand the applicable context of the deep learning influence mechanism. Meanwhile,this research also introduces the learning transfer theory,connectivism and information processing theory into the theoretical explanation of the"deep learning thinking in the Internet environment"model. The research findings also provide practical inspiration for enhancing the graduates' deep learning in the Internet environment.
引文
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[17]Viczko,M.,Fullan,M.,&Langworthy,M.(2016).A rich seam:How new pedagogies find deep learning[J].Leadership&Policy in Schools,15(2):231-233.
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[19]徐媛媛(2014).中国石油大学(华东)理科实验班学生学习方式研究[D].中国石油大学(华东):32-53
[20]曾明星,李桂平,周清平,徐洪智,董坚峰,覃遵跃,郭鑫(2016).MOOC与翻转课堂融合的深度学习场域建构[J].现代远程教育研究,(1):41-49.
[21]张浩,吴秀娟,王静(2014).深度学习的目标与评价体系构建[J].中国电化教育,(7):51-55.
[22]Zurkowsk,P.G.,何乃东,张晓娟,程璐(2017).信息服务环境:关系与重点[J].图书情报知识,(1):26-28.
[2]Baeten,M.,Kyndt,E.,Struyven,K.,&Dochy,F.(2010).Using student-centered learning environments to stimulate deep approaches to learning:Factors encouraging or discouraging their effectiveness[J].Educational Research Review,(5):243-260.
[3]Biggs,J.B.,&Collins,K.F.(1982).Evaluating the quality of learning:The SOLO Taxonomy[M].New York:Academic Press:234-253.
[4]Biggs,J.B.(2001).The revised two-factor study process questionnaire:R-SPQ-2F[J].The British Psychological Society,1:133-149.
[5]蔡吉梅,何炜华,李小平,马佳,宋曦玲,张敬敬(2014).医学学生信息素养与创新能力的相关性实证研究[J].图书情报工作,58(S2):196-198.
[6]陈晓瑞(2008).西方教育哲学流派课程与教学思想[M].北京:中国轻工业出版社:39-44.
[7]Downes,S.(2006).Learning Networks and Connective Knowledge[OB/EL].[2006-10-20].Instructional Technology Forum,92.http://it.coe.uga.edu/itforum/paper92/paper92.html.
[8]杜建霞,范斯·A·杜林汤,安东尼·A·奥林佐克,王茹(2006).动态在线讨论:交互式学习环境中的深层学习[J].开放教育研究,(4):75-79.
[9]段金菊,余胜泉(2013).学习科学视域下的e-Learning深度学习研究[J].远程教育杂志,31(4):43-51.
[10]Foasberg N M.(2015).From standards to frameworks for IL:How the ACRL framework addresses critiques of the standards[J].Portal:Libraries and the Academy,15(4):699-717.
[11]景红娜,陈琳,赵雪萍(2011).基于Moodle的深层学习研究[J].远程教育杂志,29(3):27-33.
[12]刘宇,邱慧敏(2014).网络深层学习的发展研究[J].成人教育,34(2):14-17.
[13]Podsakoff,P.M.,Mackenzie,S.B.,Lee,J.Y.,&Podsakoff,N.P.(2003).Common method biases in behavioral research:Acritical review of the literature and recommended remedies[J].Journal of Applied Psychology,88(5):879-903.doi:10.1037/0021-9101.88.5.879.
[14]Siemens,G.(2005).Connectivisim:Learning as network creation[DB/OL].ASTD Learning News,10(1).[2014-06-19].http://www.elearnspace.org/Articles/networks.html.
[15]Smith,T.W.,&Colby,S.A.(2007).Teaching for deep learning[J].Clearing House:A Journal of Educational Strategies Issues&Ideas,80(5):205-210.
[16]Spiro,R.J.,Coulson,R.,&Feltovich,P.(1988).Cognitive flexibility theory:Adavanced knowledge acquisition ill-structured domains[A].Proceedings of the Tenth Annual Conference of the Cognitive Science Society[C].Hillsdale,New Jersey:Lawrence Erlbaum Associates,375-383.
[17]Viczko,M.,Fullan,M.,&Langworthy,M.(2016).A rich seam:How new pedagogies find deep learning[J].Leadership&Policy in Schools,15(2):231-233.
[18]Wilson,K.L.,Lizzio,A.,&Ramsden,P.(1997).The development,validation and application of the Course Experience Questionnaire[J].Studies in Higher Education,22(1):33-53.
[19]徐媛媛(2014).中国石油大学(华东)理科实验班学生学习方式研究[D].中国石油大学(华东):32-53
[20]曾明星,李桂平,周清平,徐洪智,董坚峰,覃遵跃,郭鑫(2016).MOOC与翻转课堂融合的深度学习场域建构[J].现代远程教育研究,(1):41-49.
[21]张浩,吴秀娟,王静(2014).深度学习的目标与评价体系构建[J].中国电化教育,(7):51-55.
[22]Zurkowsk,P.G.,何乃东,张晓娟,程璐(2017).信息服务环境:关系与重点[J].图书情报知识,(1):26-28.
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