个性化移动学习路径优化策略应用研究被引量：38

Research on the Application of Path Optimization Strategy for Personalized Mobile Learning

在线阅读下载PDF

导出

摘要移动学习能为学习者创设个性化的移动学习环境,但移动学习过程受到学习者的学习需求、学习情境以及自身特征等多种因素影响,移动学习路径合理与否直接影响着移动学习者的学习效率。文章首先分析了移动学习环境下影响个性化学习效率的主要因素,其次提出了基于遗传算法的个性化移动学习路径优化策略,并详细阐述了基于该路径优化策略的移动学习模式,最后将研究成果应用于网络工程综合实验课程学习中,通过实证研究该移动学习路径优化策略应用的可行性和有效性。 Mobile learning can provide personalized learning environment for learners. However, the mobile learning process is affected by many factors such as learning requirement, learning context, and personality of learners. Mobile learning path directly affects learner＇s learning efficiency. In this paper, the authors first analyze the major factors that affect mobile learning efficiency. Then, they propose a path optimization strategy for personalized mobile learning based on genetic algorithm, and elaborate a mobile learning model using this optimization strategy. The authors finally report the application of this strategy in an experimental course in Network Engineering as well as the feasibility and effectiveness of the optimization strategy.

作者李浩君徐佳程房邵敏谢苏超

机构地区浙江工业大学教育科学与技术学院

出处《电化教育研究》 CSSCI 北大核心 2016年第1期39-44,共6页 E-education Research

基金 2015年度教育部人文社会科学研究青年基金项目"面向知识服务的移动设备情景感知计算机制及其实证研究"(项目编号:15YJCZH023)

关键词移动学习遗传算法个性化学习路径学习情境 Mobile Learning Genetic Algorithm Personalized Learning Path Learning Context

分类号 G434 [文化科学—教育技术学]

作者简介李浩君（1977-），男，浙江上虞人。副教授，博士研究生，主要从事移动学习、普适计算等研究。E—mail：zgdlhj@zjut．edu．cn。

引文网络
相关文献

参考文献9

1Hsu,C.C., Ho,C.C..The Design and Implementation of A Competency-Based Intelligent Mobile Learning System [J]. Expert Systems With Applications, 2012,39 (9) : 8030-8043.
2Rumetshofer,H.,WS,W.. XML-Based Adaptation Framework for Psychological-Driven E-learning Systems [J]. Educational Technology & Society,2003,6(4) : 18-29.
3Chen, C.M.. Intelligent Web-Based Learning System With Personalized Learning Path Guidance [J]. Computers & Education, 2008,51 (2) : 787-814.
4Yang,Y.J.,Wu, C.. An Attribute-Based Ant Colony System for Adaptive Learning Object Recommendation [J]. Expert Systems With Applications,2009,36(2) : 3034-3047.
5Yau ,J.Y.K. ,Joy, M..A Context-Aware Personalised M-learning Application Based on M-learning Preferences [J]. International Journal of Mobile Learning and Organisation, 2011,5 ( 1 ) : 1 - 14.
6Sha,L.,Looi,C.K.,Chen,W.,et al.Recognizing and Measuring Self-Regulated Learning in A Mobile Learning Environment[J]. Computers in Human Behavior,2012,28(2) : 718-728.
7吕琳,韩永国.多Agent的个性化学习路径推荐系统设计[J].电脑知识与技术（过刊）,2013,19(9X):5981-5984. 被引量：4
8Hwang, G.J., Kuo, F.R., Yin, P.Y., et al. A Heuristic Algorithm for Planning Personalized Learning Paths for Context-Aware Ubiquitous Learning [J]. Computers & Education,2010,54(2) : 404-415.
9Chiou,C.K.,Tseng,J.C., Hwang,G.J.,et al.An Adaptive Navigation Support System for Conducting Context -Aware Ubiquitous Learning in Museums[J].Computers & Education,2010,55(2) : 834-845.

二级参考文献9

1陈桦,麻风梅.用多Agent实现基于XML的个性化学习系统[J].微计算机信息,2008,24(9):253-255. 被引量：5
2Bohl O,Schellhase J,Sengler R,Winand U.The sharable content object reference model(SCORM) –a critical review[].Journal of Women s Health.2002
3Mu-Jung Huang,Hwa-Shan Huang,Mu-Yen Chen.Constructing a personalized e-learning system based on genetic algorithm and case-based reasoning approach[J].Expert Systems With Applications.2006(3)
4Chih-Ming Chen,Chao-Yu Liu,Mei-Hui Chang.Personalized curriculum sequencing utilizing modified item response theory for web-based instruction[J].Expert Systems With Applications.2005(2)
5F Rothlauf.Representations for genetic and evolutionary algorithms[]..2006
6Gershon.Computer Adaptive Testing[].Journal of Applied Measurement.2005
7Erdal Cayirci.Computer Assisted Exercises and Training:A Reference Guide[]..2009
8Paul Scerri.Modulating Communication to Improve Multi-agent Learning Convergence[].Dynamics of Information Systems:Algorith mic Approaches.2013
9蒋云良,徐从富.智能Agent与多Agent系统的研究[J].计算机应用研究,2003,20(4):31-34. 被引量：38