基于本体和数据挖掘技术的智能授导系统研究
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摘要
智能授导系统是借助人工智能的方法与技术,适应性地组织学习资源、实施教学策略、提供教学服务、进行教学评价的一种数字化学习支持系统。目前的智能授导系统中往往“智能化”体现不够,资源无法被有效利用,不能根据学习者个性提供相应的指导,实现个性化教学。我们希望开发一种智能的自适应授导系统,根据学习者的认知水平和学习行为,分配学习资源,制定个性化的学习路径,改变传统教育的“一视同仁”,实施个性化教育。
本文的研究工作是一项计算机应用、人工智能、教育技术学多学科交叉的研究工作。本文在教育心理学、数据挖掘和本体等方面做了较深入的研究,开展了以下主要研究工作,并取得一定的研究成果。
1、通过基于个性化教学原理的网络学习行为智能分析系统的构建和实施,积累和沉淀有分析价值的实验数据,掌握每个学习者的认知水平和学习风格等,选择ID3算法,并进行改进,分析学习者的学习者模型信息,形成学习者特征,建立个性化学习行为的决策树分类模型。
2、引入领域本体,构建智能授导系统中的学习者和学习资源相关本体模型,同时对学习资源进行语义描述,建立学习资源分配知识库,根据学习者个体特征生成个性学习导航路径,支持个性化学习。
3、实现了基于本体和数据挖掘技术的智能授导原型系统开发,包括学习行为分析及管理子系统、学习资源管理子系统、学习资源分配子系统等三个子系统。通过该系统,为每一个学习者提供了适应其需求特点的学习资源,使学习者的学习潜能在特定设计的环境下得到充分发挥。
4、论文的最后总结了本文的研究工作,并讨论了一些未解决的问题以及进一步研究工作的前景。
The Intelligent Tutoring System is a kind of digitized study support system in virtue of the artificial intelligence, it can compatibly organizes the teaching resources, implements teaching strategy, provides the teaching service, and carries on the teaching appraisal. The intellectualized degree of the present Intelligent Tutoring System is insufficient, the resources is unable to be used effectively, and it cannot provide the corresponding instruction according to the learners' individuality to realize the individual teaching. We hoped developing an auto-adapted tutoring system to assign study resources, establish individual study path, and change the " impartial treatment " of traditional education according to the cognition level and the style of learners, and then implement the individual education.
The research of this article is a crossed study of computer application, artificial intelligence, and educational technique. We have done more thorough research on the educational psychology, data mining and ontology. The main research work as follows, and obtains the certain research results.
1. Because of the constructing and implementation of the network study behavior intelligence analysis system based on individual teaching principle, we have accumulated the empirical data that have analysis value, have grasped the cognition level and the study style of each learner. We choose the ID3 algorithm, and make the improvement, then analyze the study model information, form learner study characteristic, and establish the tree classification model of individual study behavior.
2. We introduced domain ontology, and constructed the related ontology model of the learners and the study resources in the intelligent tutoring system, simultaneously carried on the semantic description to the study resources, established the study resource distribution library, and then produced individual study navigation way according to the learner's individual characteristic to support the individual study.
3. The prototype intelligent tutoring system based on the ontology and the data mining technology has been realized, including the study style analysis and management subsystem, teaching resource management subsystem, teaching resource distribution subsystem. This system provides study resources that adapted to the demands of each learner and enables the full display of study potential in the specific designed environment.
The paper finally summarized the research work of this article, and discussed some solution of question as well as the further research work prospect.
本文的研究工作是一项计算机应用、人工智能、教育技术学多学科交叉的研究工作。本文在教育心理学、数据挖掘和本体等方面做了较深入的研究,开展了以下主要研究工作,并取得一定的研究成果。
1、通过基于个性化教学原理的网络学习行为智能分析系统的构建和实施,积累和沉淀有分析价值的实验数据,掌握每个学习者的认知水平和学习风格等,选择ID3算法,并进行改进,分析学习者的学习者模型信息,形成学习者特征,建立个性化学习行为的决策树分类模型。
2、引入领域本体,构建智能授导系统中的学习者和学习资源相关本体模型,同时对学习资源进行语义描述,建立学习资源分配知识库,根据学习者个体特征生成个性学习导航路径,支持个性化学习。
3、实现了基于本体和数据挖掘技术的智能授导原型系统开发,包括学习行为分析及管理子系统、学习资源管理子系统、学习资源分配子系统等三个子系统。通过该系统,为每一个学习者提供了适应其需求特点的学习资源,使学习者的学习潜能在特定设计的环境下得到充分发挥。
4、论文的最后总结了本文的研究工作,并讨论了一些未解决的问题以及进一步研究工作的前景。
The Intelligent Tutoring System is a kind of digitized study support system in virtue of the artificial intelligence, it can compatibly organizes the teaching resources, implements teaching strategy, provides the teaching service, and carries on the teaching appraisal. The intellectualized degree of the present Intelligent Tutoring System is insufficient, the resources is unable to be used effectively, and it cannot provide the corresponding instruction according to the learners' individuality to realize the individual teaching. We hoped developing an auto-adapted tutoring system to assign study resources, establish individual study path, and change the " impartial treatment " of traditional education according to the cognition level and the style of learners, and then implement the individual education.
The research of this article is a crossed study of computer application, artificial intelligence, and educational technique. We have done more thorough research on the educational psychology, data mining and ontology. The main research work as follows, and obtains the certain research results.
1. Because of the constructing and implementation of the network study behavior intelligence analysis system based on individual teaching principle, we have accumulated the empirical data that have analysis value, have grasped the cognition level and the study style of each learner. We choose the ID3 algorithm, and make the improvement, then analyze the study model information, form learner study characteristic, and establish the tree classification model of individual study behavior.
2. We introduced domain ontology, and constructed the related ontology model of the learners and the study resources in the intelligent tutoring system, simultaneously carried on the semantic description to the study resources, established the study resource distribution library, and then produced individual study navigation way according to the learner's individual characteristic to support the individual study.
3. The prototype intelligent tutoring system based on the ontology and the data mining technology has been realized, including the study style analysis and management subsystem, teaching resource management subsystem, teaching resource distribution subsystem. This system provides study resources that adapted to the demands of each learner and enables the full display of study potential in the specific designed environment.
The paper finally summarized the research work of this article, and discussed some solution of question as well as the further research work prospect.
引文
[1]祝智庭,张屹,林阳.中华人民共和国国家标准的术语规范(报批稿)[S].广州:华东师范大学,2003.
[2]Carbonell J R.AI in CAI:An artificial intelligence approach to computer aided instruction[C].IEEE Transaction Machine Systems,1970,11(4):190-202.
[3]陈天云,张剑平.智能教学系统(ITS)的研究现状及其在中国的发展[J].中国电化教育2007,(2):95-99.
[4]莫赞,冯珊,唐超.智能教学系统的发展与前瞻[J].计算机工程与应用,2002,(6):628.
[5]冯红,杨卉,王陆.ITS中基于纠错诊断的知识表示模型[J].计算机工程与应用,2004,33:212-214.
[6]曲红亭,申瑞民.基于数据挖掘的个性化学习导航系统的设计与实现[J].计算机工程,2003,5:59-61.
[7]周晓军,黄海燕,张普.智能教学系统中的知识树增长模型[J].计算机研究与发展,2001,38(10):1217-1223.
[8]邓晖,徐梅林.网络学习环境之个性化属性调查及启示[J].现代教育技术,2003,1:49-54.
[9]陈品德.基于Web的适应性学习支持系统研究[D].华南师范大学,2003
[10]常子冠.个性化学习支持系统中教学策略编辑工具的设计与开发[D].首都师范大学,2007
[11]Aleven,V.,McLaren,B.,Sewall,J.,Koedinger,K.R.The Cognitive Tutor Authoring Tools(CTAT):Preliminary.evaluation of efficiency gains[A].M.Ikeda,K.Ashley,& T.W.Chan(Eds.),Intelligent Tutoring Systems 2006[C].LNCS 4053(pp.61-70.)Berlin:Springer-Verlag.2006.61-70.
[12]Murray,B.Intelligent Tutoring Systems for Commercial Games:The Virtual Combat Training Center Tutor and Simulation[A].Proceedings of the Second Artificial Intelligence and Interactive Digital Entertainment Conference[C].Menlo Park,CA:AAAI Press.2006.66-71.
[13]Vincent Aleven,Bruce McLaren,Ido Roll,Kenneth Koedinger.Toward Tutoring Help Seeking:Applying Cognitive Modeling to Meta-cognitive skills[A].Proceedings of the Seventh International Conference on Intelligent Tutoring Systems[C].LNCS 3220.Berlin:Springer-Verlag 2004.227-239.
[14]刘巍.远程学习策略指导研究现状[J].远程教育杂志,2006,(6):52-56
[15]智勇.分布式学习环境中的智能授导系统研究[D].南京:南京师范大学,2004.
[16]乔向杰..基于Web和数据挖掘的智能教学系统的研究与开发:硕士学位[D].中国优秀博硕士学位论文全文数据库.首都师范大学,2005.
[17]员巧云,程刚.近年来我国数据挖掘研究综述[J].情报学报,2005,(02)250-256
[18]程志,桂占吉.Web挖掘的方法及教育应用[J].中国电化教育,2006.7:98-101
[19]刘红岩,陈剑,陈国清.挖掘中的数据分类算法综述.清华大学学报(自然科学版),2002,42(6):727-730
[20]杜华英,赵跃龙.人工神经网络典型模型的比较研究[J]计算机技术与发展,2006,(05).97-99
[21]朱绍文等.决策树采掘技术及发展趋势。计算机工程。2002,28(8):77-78
[22]冯洁.Web 日志挖掘相关算法研究及其原型系统设计[D].西南交通大学,2007.
[23]王越.基于Ontology的Web政务资源的智能处理与应用[D].山东大学,2007
[24]Studer R,Benjamins V R,Fensel D.Knowledge Engineering,Principles and Met-hods.Data and Knowledgeing.1998,25(122):161-197
[25]Dejan Milojicic.Mobile agent application from Trend Wars.IEEE Concurrency.2000(11):12-16
[26]杨秋芬,陈跃新.Ontology方法学综述.计算机应用研究,2002,4(4):5-7
[27]Martino' Connor,Holger Knublauch,Samson Tu,etal.Stanford Medical Informatics[C].Stanford:Stanford University School of Medicine,2005.
[28]俞时,异构资源中基于本体的信息互操作性研究,东华大学博士学位论文2003.4
[29]李文斌,刘椿年,陈嶷瑛.对OWL及其逻辑基础的研究[J].计算机应用,2004,(12):146-148
[30]胡鹤,刘大有,王生生.Web本体语言OWL[J].计算机工程,2004,30(12):1-2
[31]W3C.OWL Web Ontology Language Overview[EB/OL].10-February-2004http://www.w3.org/TR/2004/REC-owl-features-20040210/
[32]W3C.OWL Web Ontology Language Guide[EB/OL].http://www.w3.org/TR/owl-guide/,2004
[33]J.J.Carroll and J.D.Roo.Web Ontology Language(OWL)Test Cases[EB/OL].http://www.w3.org/TR/owl-test/,2003.
[34]Ding Y,Foo S.Ontology Research and Development:Part 1—A Review of Ontology Generation[J].Journal of Information Science,2002,28(2):123-136
[35]严亚兰,张金隆.基于OWL的多媒体本体构建探索[J].计算机工程与应用,2006年28期:44-46
[36]Ding Y,Foo S.Ontology Research and Development:Part 2—A Review of Ontology Mapping and Evolving[J].Journal of Information Science,2002,28(5):383-396
[37]郭景峰等.决策树算法的并行性研究[J].计算机工程.2002,28(8):77-78
[38]Pnertzas,J,Hatzilygerud,I.Rule basedu Pdaetmhetods or fahybridurle base.Data & Knoweldge Engnieering,2005(55).103
[39]吴钢.现代教育评价基础[M].上海:学林出版社,2004.
[40]杨丹.基于《学习者模型规范》的网络教育学生模型库的研究与设计[J].现代远距离教育,2005,(04).
[41]Tan Zi-Jing,Shi Bo-Le.Propagating Functional Dependency and Normalization Between Relations and XML.Journal of Software,2005,16 4:533-539.
[42]N.Noy,M.Sintek,S.Decker,et al.Creating Semantic Web contents with Protege-2000[J].IEEE Intelligent Systems.2001,2(16):60-71.
[43]丁晟春,顾德访.Jena在实现基于Ontology的语义检索中的应用研究[J]:现代图书情报技术:2005年10期:9-13.
[44]何克抗,师书恩.计算机辅助教育[M].北京:高等教育出版社,2003.
[45]靳强勇,李冠宇,张俊.异构数据集成技术的发展和现状明[J].计算机工程 与应用,2002-11
[46]Aroyo L,Cristea A,Dicheva D.A layered approach towards domain authoring support[C].ICAI102,Las Vegas,US,2002.
[2]Carbonell J R.AI in CAI:An artificial intelligence approach to computer aided instruction[C].IEEE Transaction Machine Systems,1970,11(4):190-202.
[3]陈天云,张剑平.智能教学系统(ITS)的研究现状及其在中国的发展[J].中国电化教育2007,(2):95-99.
[4]莫赞,冯珊,唐超.智能教学系统的发展与前瞻[J].计算机工程与应用,2002,(6):628.
[5]冯红,杨卉,王陆.ITS中基于纠错诊断的知识表示模型[J].计算机工程与应用,2004,33:212-214.
[6]曲红亭,申瑞民.基于数据挖掘的个性化学习导航系统的设计与实现[J].计算机工程,2003,5:59-61.
[7]周晓军,黄海燕,张普.智能教学系统中的知识树增长模型[J].计算机研究与发展,2001,38(10):1217-1223.
[8]邓晖,徐梅林.网络学习环境之个性化属性调查及启示[J].现代教育技术,2003,1:49-54.
[9]陈品德.基于Web的适应性学习支持系统研究[D].华南师范大学,2003
[10]常子冠.个性化学习支持系统中教学策略编辑工具的设计与开发[D].首都师范大学,2007
[11]Aleven,V.,McLaren,B.,Sewall,J.,Koedinger,K.R.The Cognitive Tutor Authoring Tools(CTAT):Preliminary.evaluation of efficiency gains[A].M.Ikeda,K.Ashley,& T.W.Chan(Eds.),Intelligent Tutoring Systems 2006[C].LNCS 4053(pp.61-70.)Berlin:Springer-Verlag.2006.61-70.
[12]Murray,B.Intelligent Tutoring Systems for Commercial Games:The Virtual Combat Training Center Tutor and Simulation[A].Proceedings of the Second Artificial Intelligence and Interactive Digital Entertainment Conference[C].Menlo Park,CA:AAAI Press.2006.66-71.
[13]Vincent Aleven,Bruce McLaren,Ido Roll,Kenneth Koedinger.Toward Tutoring Help Seeking:Applying Cognitive Modeling to Meta-cognitive skills[A].Proceedings of the Seventh International Conference on Intelligent Tutoring Systems[C].LNCS 3220.Berlin:Springer-Verlag 2004.227-239.
[14]刘巍.远程学习策略指导研究现状[J].远程教育杂志,2006,(6):52-56
[15]智勇.分布式学习环境中的智能授导系统研究[D].南京:南京师范大学,2004.
[16]乔向杰..基于Web和数据挖掘的智能教学系统的研究与开发:硕士学位[D].中国优秀博硕士学位论文全文数据库.首都师范大学,2005.
[17]员巧云,程刚.近年来我国数据挖掘研究综述[J].情报学报,2005,(02)250-256
[18]程志,桂占吉.Web挖掘的方法及教育应用[J].中国电化教育,2006.7:98-101
[19]刘红岩,陈剑,陈国清.挖掘中的数据分类算法综述.清华大学学报(自然科学版),2002,42(6):727-730
[20]杜华英,赵跃龙.人工神经网络典型模型的比较研究[J]计算机技术与发展,2006,(05).97-99
[21]朱绍文等.决策树采掘技术及发展趋势。计算机工程。2002,28(8):77-78
[22]冯洁.Web 日志挖掘相关算法研究及其原型系统设计[D].西南交通大学,2007.
[23]王越.基于Ontology的Web政务资源的智能处理与应用[D].山东大学,2007
[24]Studer R,Benjamins V R,Fensel D.Knowledge Engineering,Principles and Met-hods.Data and Knowledgeing.1998,25(122):161-197
[25]Dejan Milojicic.Mobile agent application from Trend Wars.IEEE Concurrency.2000(11):12-16
[26]杨秋芬,陈跃新.Ontology方法学综述.计算机应用研究,2002,4(4):5-7
[27]Martino' Connor,Holger Knublauch,Samson Tu,etal.Stanford Medical Informatics[C].Stanford:Stanford University School of Medicine,2005.
[28]俞时,异构资源中基于本体的信息互操作性研究,东华大学博士学位论文2003.4
[29]李文斌,刘椿年,陈嶷瑛.对OWL及其逻辑基础的研究[J].计算机应用,2004,(12):146-148
[30]胡鹤,刘大有,王生生.Web本体语言OWL[J].计算机工程,2004,30(12):1-2
[31]W3C.OWL Web Ontology Language Overview[EB/OL].10-February-2004http://www.w3.org/TR/2004/REC-owl-features-20040210/
[32]W3C.OWL Web Ontology Language Guide[EB/OL].http://www.w3.org/TR/owl-guide/,2004
[33]J.J.Carroll and J.D.Roo.Web Ontology Language(OWL)Test Cases[EB/OL].http://www.w3.org/TR/owl-test/,2003.
[34]Ding Y,Foo S.Ontology Research and Development:Part 1—A Review of Ontology Generation[J].Journal of Information Science,2002,28(2):123-136
[35]严亚兰,张金隆.基于OWL的多媒体本体构建探索[J].计算机工程与应用,2006年28期:44-46
[36]Ding Y,Foo S.Ontology Research and Development:Part 2—A Review of Ontology Mapping and Evolving[J].Journal of Information Science,2002,28(5):383-396
[37]郭景峰等.决策树算法的并行性研究[J].计算机工程.2002,28(8):77-78
[38]Pnertzas,J,Hatzilygerud,I.Rule basedu Pdaetmhetods or fahybridurle base.Data & Knoweldge Engnieering,2005(55).103
[39]吴钢.现代教育评价基础[M].上海:学林出版社,2004.
[40]杨丹.基于《学习者模型规范》的网络教育学生模型库的研究与设计[J].现代远距离教育,2005,(04).
[41]Tan Zi-Jing,Shi Bo-Le.Propagating Functional Dependency and Normalization Between Relations and XML.Journal of Software,2005,16 4:533-539.
[42]N.Noy,M.Sintek,S.Decker,et al.Creating Semantic Web contents with Protege-2000[J].IEEE Intelligent Systems.2001,2(16):60-71.
[43]丁晟春,顾德访.Jena在实现基于Ontology的语义检索中的应用研究[J]:现代图书情报技术:2005年10期:9-13.
[44]何克抗,师书恩.计算机辅助教育[M].北京:高等教育出版社,2003.
[45]靳强勇,李冠宇,张俊.异构数据集成技术的发展和现状明[J].计算机工程 与应用,2002-11
[46]Aroyo L,Cristea A,Dicheva D.A layered approach towards domain authoring support[C].ICAI102,Las Vegas,US,2002.