[1]程 艳,解建华,谭平飞,等.面向虚拟学习社区的学习行为特征挖掘与分组方法的研究[J].江西师范大学学报(自然科学版),2016,40(06):640-643.
　CHENG Yan,XIE Jianhua,TAN Pingfei,et al.Learning Behavior Feature Mining and Grouping Method for Virtual Learning Community[J].Journal of Jiangxi Normal University:Natural Science Edition,2016,40(06):640-643.
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面向虚拟学习社区的学习行为特征挖掘与分组方法的研究()
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《江西师范大学学报》（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2016年06期
页码:
640-643
栏目:
出版日期:
2016-12-01

文章信息/Info

Title:
Learning Behavior Feature Mining and Grouping Method for Virtual Learning Community
作者:
程 艳; 解建华; 谭平飞; 杨志明
1.江西师范大学计算机信息工程学院,江西 南昌 330022; 2.同济大学计算机科学与技术博士后流动站,上海 201804
Author(s):
CHENG Yan; XIE Jianhua; TAN Pingfei; YANG Zhiming
1.College of Computer and Information Engineering,Jiangxi Normal University,Nanchang Jiangxi 330022,China; 2.Computer Science and Technology Post Doctoral Mobile Station,Tongji University,Shanghai 201804,China
关键词:
虚拟学习社区;  模糊c均值聚类算法;  学习特征;  个性化教学
Keywords:
virtual learning community;  fuzzy ans clustering algorithm;  learning characteristics;  personalized teaching
分类号:
TP 391
摘要:
虚拟学习社区作为网络教育的一种新兴模式,越来越受到人们的关注.如何为不同的学习者提供良好的个性化教学服务是虚拟学习社区研究的重要问题,而学习者的学习特征的提取与分析是个性化教学的基础.以虚拟学习社区为背景,从学习者的学习过程和学习特征入手,运用模糊c均值聚类算法(FCM)挖掘并分析学习过程中学习者的学习特征,进而根据学习者的知识水平、自主学习和协作学习积极性等学习特征进行精确分组划分,以达有针对性的教学指导,实现个性化教学,提高学习者学习效率.
Abstract:
Virtual learning community,as a new mode of network education,has attracted more and more attention.How to provide a good teaching service for different learners is an important issue in the virtual learning community,and the extraction and analysis of the characteristics of the learners are the basis of the individualized teaching.It starts from the learner’s learning process and learning characteristics,using the fuzzy c-means clustering algorithm(FCM),mining and analyzing the learning features of students in the learning process in the background of the virtual learning community.Students are accurate grouped according to the learner’s knowledge level,autonomous learning and cooperative learning initiative and other learning characteristics in order to achieve the goal of personalized teaching,to improve the learning efficiency of the learners.Key words:virtual learning community; fuzzy c-means clustering algorithm(FCM),mining and analyzing the learning features of students in the learning process in the background of the virtual learning community.Students are accurate grouped according to the learner’s knowledge level,autonomous learning and cooperative learning initiative and other learning characteristics in order to achieve the goal of personalized teaching,to improve the learning efficiency of the learners.

参考文献/References:

[1] 江吉林.新媒体时代大学生网络学习特征分析 [J].软件导刊:教育技术,2015(2):54-56.
[2] 刘砚.网络学习者学习特征、影响因素及对策研究 [J].天津职业院校联合学报,2013(7):47-50.
[3] 张杰.虚拟学习社区中学习者特征的分析研究 [J].电化教育研究,2008(12):67-71.
[4] 王剑,陈涛.个性化e-Learning协作学习推荐系统研究 [J].中国远程教育,2016(7):1-9.
[5] 尹晨.e-Learning协作学习中分组策略研究 [J].计算机技术与发展,2012(12):55-58.
[6] 程艳,许维胜,杨继君,等.基于本体兴趣特征向量空间模型的社区自组织法[J].系统工程,2009(5):96-103.
[7] 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.
[8] 赵喜庆,王发成.个性化教学促进一般生源特长发展研究 [J].现代中小学教育,2015(11):11-13.
[9] Viktor Freiman,Nicole Lirette-Pitre.Building a virtual learning community of problem solvers:example of CASMI community [J].ZDM,2009,41(41):245-256.
[10] Bezdek J.Pattern recognition with Fuzzy Objective Function Algorithms [M].New york:Plenum Press,1981.
[11] 孙晓霞,刘晓霞,谢倩茹.模糊c-均值(FCM)聚类算法的实现 [J].计算机应用与软件,2008(3):48-50.
[12] 高新波,李洁,谢维信.模糊c均值聚类算法中参数m的优选 [J].模式识别与人工智能,2000(1):7-11.
[13] 赵卫中,马慧芳,李志清,等.一种结合主动学习的半监督文档聚类算法 [J].软件学报,2012(6):1486-1499.

备注/Memo

备注/Memo:
收稿日期:2016-10-02基金项目:国家自然科学基金(61262080),江西省科技支撑计划重点项目(20151BBE50121)和江西省教育厅科技重点课题(GJJ15029)资助项目.作者简介:程 艳(1976-),女,江西婺源人,教授,博士,主要从事虚拟社区和数据挖掘等方面的研究.
更新日期/Last Update: 1900-01-01