基于LSA与SNA的虚拟学习社区信息交互实证研究
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摘要
随着互联网的普及,网络环境下的虚拟学习已成为一种重要的学习方式,虚拟环境中的交互对于提升学习效果具有重要意义。传统研究者大多使用总结性评价方法而无法触及到交互具体过程与细节,滞后序列分析法为人们深入探究交互过程提供了关键性技术方法。基于滞后序列分析法,并结合社会网络分析法,针对虚拟学习社区中参与者的交互行为序列开展滞后序列分析,进而由点及线地深入探究参与者的信息交互特征。实证结果表明,参与者的信息交互行为过程存在明显特征,网络平台设计者与教师可以从关键行为强化与无关行为控制角度优化虚拟学习社区,并对学习者进行更具针对性的指导,提升虚拟学习社区参与者间的信息交互效率,最终促进虚拟学习社区的发展。
With the popularization of Internet,virtual learning in network environment has become an important learning method,and interaction in virtual environment is of great significance for improving learning effect.Most of the previous researchers use summative evaluation method,which can not reach the interaction process and the specific details,while lagging sequence analysis method provides the key technology and methods to further explore the process of interaction.Based on LSA and connecting with the social network analysis,we carry out interaction sequence backward sequence analysis for different groups,then delve into the information interaction characteristics of different groups gradually.The empirical results show that the information interaction behavior of participants has obvious characteristics.Network platform designers and teachers can focus on key actions and control irrelevant behavior to optimize the virtual learning community,and carry out more specific guidance for learners,improve efficiency of virtual learning community information interaction between participants and finally promote the development of virtual learning community.
With the popularization of Internet,virtual learning in network environment has become an important learning method,and interaction in virtual environment is of great significance for improving learning effect.Most of the previous researchers use summative evaluation method,which can not reach the interaction process and the specific details,while lagging sequence analysis method provides the key technology and methods to further explore the process of interaction.Based on LSA and connecting with the social network analysis,we carry out interaction sequence backward sequence analysis for different groups,then delve into the information interaction characteristics of different groups gradually.The empirical results show that the information interaction behavior of participants has obvious characteristics.Network platform designers and teachers can focus on key actions and control irrelevant behavior to optimize the virtual learning community,and carry out more specific guidance for learners,improve efficiency of virtual learning community information interaction between participants and finally promote the development of virtual learning community.
引文
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[15]戴心来,郭卡,刘蕾.MOOC学习者满意度影响因素实证研究——基于“中国大学MOOC”学习者调查问卷的结构方程分析[J].现代远距离教育,2017(2):17-23.
[2]尚建新,解月光,王伟.虚拟学习社区中学习者交互因素研究[J].电化教育研究,2010(8):65-70.
[3]陈丽.远程学习的教学交互模型和教学交互层次塔[J].中国远程教育,2004(3):24-28.
[4]路林林,李兴保,宋燕.校园教育辅助类虚拟学习社区交互研究[J].远程教育杂志,2013(1):106-112.
[5]赖文华,叶新东.虚拟学习社区中知识共享的社会网络分析[J].现代教育技术,2010(10):97-101.
[6]宋学峰,赵蔚,高琳,等.社交问答网站知识共享的内容及社会网络分析[J].现代教育技术,2014(6):70-77.
[7]杨现民,王怀波,李冀红.滞后序列分析法在学习行为分析中的应用[J].中国电化教育,2016(2):17-23,32.
[8]梁云真,赵呈领,阮玉娇,等.网络学习空间中交互行为的实证研究——基于社会网络分析的视角[J].中国电化教育,2016(7):22-28.
[9]戴心来,王丽红,崔春阳,等.基于学习分析的虚拟学习社区社会性交互研究[J].电化教育研究,2015(12):59-64.
[10] SACKETT G P.Observing behavior:theory and applications in mental retardation[M].Baltimore:University Park Press,1978.
[11] HAWKS I K.Facilitativeness in small groups:aprocess-oriented study using lag sequential analysis[J].Psychological reports,1987,61(3):955-962.
[12] HILLMAN D C A,WILLIS D J,GUNAWARDENA C N.Learner-interface interaction in distance education:an extension of contemporary models and strategies for practitioners[J].American journal of distance education,1994,8(2):30-42.
[13] BAKEMAN R.Observing interaction:an introduction to sequential analysis[M].Cambridge:Cambridge university press,1997.
[14]胥果.运用学习分析技术促进网络教育平台发展[J].软件导刊,2013(12):184-186.
[15]戴心来,郭卡,刘蕾.MOOC学习者满意度影响因素实证研究——基于“中国大学MOOC”学习者调查问卷的结构方程分析[J].现代远距离教育,2017(2):17-23.