自适应学习系统中学习者模型的表示及特征值获取方法研究
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摘要
随着信息技术与社会科学的快速发展,E-Learning正以一种越来越普遍的学习方式走进学校教育及家庭教育。自适应学习系统也呼之而出,它从学习者差异为出发点,根据每个学习者的不同特点为其提供适合的学习环境、学习活动、学习过程。在自适应系统中,最为关键的环节就是学习者模型的建立。而目前大多数学习者模型主要存在着关注维度不够科学、表示方法可计算性较差、特征值获取方法单一且主观的问题.这些问题的存在,容易导致学习者的能力与建议学习资源难度水平不匹配,甚至导致学习者在学习中的认知超负荷或迷失。本文主要针对以上问题开展研究,旨在通过学习者模型的表示和获取方法的研究,构建合理有效的模型,为自适应学习提供有效支撑。
本文首先对国内外自适应学习系统进行了分析研究,总结得出了自适应学习系统的设计原则。基于此原则,提出了自适应学习系统的一般体系结构,并分析了学习者模型在系统中的重要性。
其次,基于研究定位,以相关的教育理论为支撑,提出了一种由知识水平、认知能力和偏好信息三个要素(特征项)构成的新的学习者模型AL(MAdvanced Learner Model),并分别给出了采用集合和序偶的方法对这三个特征进行表示的方法。之后,分别给出了ALM中三个特征项的特征值获取方法,即综合运用模糊逻辑理论、线性计算方法、空间向量的方法对学习者的知识水平、认知能力和偏好信息分别进行估算,以获取相应的特征值。从多角度多方法来构建学习者模型,并给出了ALM初始化和演化的过程。
最后,对ALM进行了应用案例研究,提出了基于ALM的自适应学习系统NalsALM的设计及工作原理,并以学习体育知识为例对该系统的效果进行了评估。实验研究表明,该模型可以根据学习者的目标、已有水平、能力、个性特征等因素实现学习资源有效的自组织和推送,满足学习者个性化的学习需求。
Along with the information technology and social sciences' fast development, E-Learning is an increasingly popular way of learning into the school education and family education. In this context, adaptive learning system for out call it different from the learner as the starting point, according to the different characteristics of each learner to provide a suitable learning environment, learning activities, learning process. In an adaptive system, the most critical aspect is the construction of learner model. Most of learner model is mainly the existence of such problems, not enough scientific, poor computability of representation and a single and subjective Characteristic value acquisition method. so that lead to a lack of satisfaction about the result of deducing , Even cause learner’s cognitive overload or disorientation. In this paper, we carry out research in the light of these problems. Learner model aims to construct a reasonable and effective model base on the research of represent and acquisition method for adaptive learning to provide effective support.
In the first place, conclusion is drawn that the adaptive learning system designing principles and general architecture based on the domestic and adaptive learning system analysis. And analyzes the importance of learner model in the system.
Next, we propose a new learner model called ALM(Advanced Learner Model)which is consisted of knowledge level, cognitive ability and preferences, based on research position and the related theory. Give the representation method respectively by the collection and ordered pair. And respectively introduce the acquisition method of the three characteristic value of ALM based on fuzzy logic theory, linear method and space vector. Then describes the initialization and evolution of the ALM process.
Finally,we propose an adaptive learning system called NalsALM based on ALM. Respectively introduce the designing method and the realizing method of NalsALM. And take the physical learning as example to evaluate the effect of the system. Experimental studies have shown that the model can achieve self-organization and the push based on learner objectives, knowledge level, ability, personality characteristics and other factors of effective learning resources to meet the learning needs of individual learners.
本文首先对国内外自适应学习系统进行了分析研究,总结得出了自适应学习系统的设计原则。基于此原则,提出了自适应学习系统的一般体系结构,并分析了学习者模型在系统中的重要性。
其次,基于研究定位,以相关的教育理论为支撑,提出了一种由知识水平、认知能力和偏好信息三个要素(特征项)构成的新的学习者模型AL(MAdvanced Learner Model),并分别给出了采用集合和序偶的方法对这三个特征进行表示的方法。之后,分别给出了ALM中三个特征项的特征值获取方法,即综合运用模糊逻辑理论、线性计算方法、空间向量的方法对学习者的知识水平、认知能力和偏好信息分别进行估算,以获取相应的特征值。从多角度多方法来构建学习者模型,并给出了ALM初始化和演化的过程。
最后,对ALM进行了应用案例研究,提出了基于ALM的自适应学习系统NalsALM的设计及工作原理,并以学习体育知识为例对该系统的效果进行了评估。实验研究表明,该模型可以根据学习者的目标、已有水平、能力、个性特征等因素实现学习资源有效的自组织和推送,满足学习者个性化的学习需求。
Along with the information technology and social sciences' fast development, E-Learning is an increasingly popular way of learning into the school education and family education. In this context, adaptive learning system for out call it different from the learner as the starting point, according to the different characteristics of each learner to provide a suitable learning environment, learning activities, learning process. In an adaptive system, the most critical aspect is the construction of learner model. Most of learner model is mainly the existence of such problems, not enough scientific, poor computability of representation and a single and subjective Characteristic value acquisition method. so that lead to a lack of satisfaction about the result of deducing , Even cause learner’s cognitive overload or disorientation. In this paper, we carry out research in the light of these problems. Learner model aims to construct a reasonable and effective model base on the research of represent and acquisition method for adaptive learning to provide effective support.
In the first place, conclusion is drawn that the adaptive learning system designing principles and general architecture based on the domestic and adaptive learning system analysis. And analyzes the importance of learner model in the system.
Next, we propose a new learner model called ALM(Advanced Learner Model)which is consisted of knowledge level, cognitive ability and preferences, based on research position and the related theory. Give the representation method respectively by the collection and ordered pair. And respectively introduce the acquisition method of the three characteristic value of ALM based on fuzzy logic theory, linear method and space vector. Then describes the initialization and evolution of the ALM process.
Finally,we propose an adaptive learning system called NalsALM based on ALM. Respectively introduce the designing method and the realizing method of NalsALM. And take the physical learning as example to evaluate the effect of the system. Experimental studies have shown that the model can achieve self-organization and the push based on learner objectives, knowledge level, ability, personality characteristics and other factors of effective learning resources to meet the learning needs of individual learners.
引文
[1]何克抗.从信息时代的教育与培训看教学设计理论的新发展(上)[J].中国电化教育,1998,10: 9-12.
[2]何克抗.从信息时代的教育与培训看教学设计理论的新发展(中)[J].中国电化教育,1998,11: 9-16.
[3]何克抗.从信息时代的教育与培训看教学设计理论的新发展(下)[J].中国电化教育,1998,12: 9-13.
[4]徐素霞. E-Learning中学习者建模研究[D].武汉:华中师范大学,2007.
[5]史元春.以规矩促发展[N].计算机世界, 2002-07-22(B09).
[6]高鹏.基于数据挖掘的个性化网络教学平台研究[D].西安:西北大学,2005
[7]奚建清,朱斌,陈鹏,张宗杰,文志康.现代远程教育中学习者的相关规范[J].中国远程教育,2002,2:17-19
[8] PeterDolog,NicolaHenze,WolfgangNejdl,et al. Personalization in Distributed E-Learning environments,Proeeedings of the 13th international World Wide Web conference on Alternate track Papers & Posters,2004,5:170-179.
[9]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,2005,4:28-29.
[10]网络教育技术规范(CELTS).[EB/OL].http://www.docin.com/p-10487426.html.
[11]何克抗.建构主义──革新传统教学的理论基础[J].科学课:小学版,2003,12:22-23.
[12]何克抗.建构主义——革新传统教学的理论基础(二)[J].科学课:小学版,2004,1:46-47.
[13] ONASSEND, DAVIDSON M, COLLINS M, et al. Constructivism and computer-mediated communication in distance education [J]. American journal of distance education, 1995, 9(2): 7-26.
[14]模糊逻辑简介.[EB/OL].http://210.40.32.30/gzzy/ArticleShow.asp?ArticleID=1322
[15]张云涛,龚玲.数据挖掘原理与技术[M].北京:电子工业出版社,2004
[16]刘桓,曹红菊.自适应学习系统的研究与设计[J].软件导刊,2006,6:39-41.
[17] Brusilovsky. Adaptive Educational Systems on the World - Wide - Web: A Review of Available Technologies. Proceedings of Workshop "WWW - Based Tutoring" at 4th International Conference on Intelligent Tutoring Systems (ITS'98), San Anto (1998)nio, TX, 08.
[18]余胜泉.适应性学习——远距离教育发展的趋势[J].开放教育研究,2000,3:11-15.
[19] FONSECA F, EGENHOFER M, AGOURIS P, et al. Using ontologies for integrated geographic information systems [J]. Transactions in GIS, 2002, 6(3): 231-57.
[20] A Méndez-Vilas, A Solano, J Mesa and JA Mesa. Current Developments in Technology-Assisted Education, 2006, 1:260-264
[21] Jia B,Zhong SC,Zheng TY,et al. The Study and Design of Adaptive Learning System Based on Fuzzy Set Theory,in press.
[22]汪晓岩,胡庆生,李斌,等.面向Internet的个性化智能信息检索[J].计算机研究与发展,1999,36(9):1039-1046.
[23]李铮,赵桂钦.ICAI系统学习者建模的研究[J].计算机工程与科学,2002,3:101-104.
[24]来兴平,伍永平.采煤学多媒体智能CAI系统的设计与实现[J].计算机系统应用,1997,2:34-35.
[25]周春萍,周相泉.基于贝叶斯网络的自适应学生模型的研究[J].山东轻工业学院学报(自然科学版),2007,4:3-6.
[26]陈庚,安玉洁,李亚春等.远程学习者特征研究的现状[J].《中国远程教育》, 2005,11:31-33.
[27] RM加涅,LJ布里格斯,WW韦杰著皮连生,庞维国等译,教学设计原理[M]华东师范大学出版社,2001.
[28]冯红,王陆,杨卉.多目标的学习者模型研究[J].计算机工程与应用,2003,36:98-100.
[29]刘通江.个性化课件生成系统中动态学生模型的研究[D].北京:首都师范大学,硕士学位论文,2004.
[30]刘艺.智能教学系统中学生模型的构建[J].丹东纺专学报,2005, 1:64-67.
[31]冯锐.关于网络教学中学生特征知识分析的探讨.甘肃广播电视大学学报[J], 2007,17(2):3-6.
[32]李镇西,李广生.莫把谈话作谈心[J].班主任,2003,7:41-42.
[33]李翠云.罗伯特·加涅作为丰碑和旗帜挺立.呼伦贝尔学院学报,2006,4:30-33.
[34] Jia B,Zhong SC,Zheng TY,et al.The Construction and Evolution of Learner Model in Adaptive Learning System[C]. In:Hj. Kamaruzaman Jusoff, eds.Proc. of The 2009 International Conference on Computer Technology and Development (ICCTD 2009),USA:IEEE.2009.148-152.
[35]庄致.自适应远程教学系统中学生认知水平估算方法[J].计算机工程与应用,2007,3:281-284.
[36]唐素勤,钟智.学生认知能力的评估[J].广西科学院学报,2002,4:281-284.
[37]姜曾贺,吴战杰.网络环境下多维学习者特征分析模型的构建[J].电化教育研究,2005, 4:71-73.
[38]吴战杰.网络远程教育中学习者特征分析体系的构建及学生模型的设计[D].陕西师范大学.2004.
[39]赵以涛,杨雪.基于网络教育的学习者特征分析系统的设计与实现[J].中小学电教,2006,12:56-58.
[40]朱斌,文志康.学习者模型标准的研究与应用[J].《计算机工程》,2002,Z1:300-303.
[41]孙志伟.基于学习者特征的个性化学习支持系统的研究[D].天津师范大学.2009.
[42] CLAYPOOL M, LE P, WASED M, et al. Implicit interest indicators[C], F, 2001. ACM New York, NY, USA.
[43]胡运安,吕智慧,吴杰等.基于SCORM的学习行为采集模型的设计与实现[J].计算机工程与应用,2004,33:106-108.
[44]杨卉,王陆.基于网络的个性化学习系统中学习者个性特征的提取算法[J].计算机工程与应用,2003,25:179-181.
[45]赵英姿.基于用户行为模式分析的个性化学习支持系统[J].职业教育研究,2006,6,122-123.
[46]冯锐.网络学习支持系统中学生特征分析模型的构建及技术实现[J].中国电化教育,2006,12:31-33.
[47] NAING M, LIM E, GOH D. Ontology-based Web annotation framework for hyperlink structures [J]. Proceedings of WISE Workshops 2002, 2002, 184-93.
[48] LIU Z, LIU L, KANG H, et al. An Ontology-Based Method of Adaptive Learning, F, 2009 [C].
[49]刘志勇,刘磊,刘萍萍,杨帆,贾冰.一种基于语义网的个性化学习资源推荐算法[J].吉林大学学报工学版增刊,2009,39(2): 391-395.
[2]何克抗.从信息时代的教育与培训看教学设计理论的新发展(中)[J].中国电化教育,1998,11: 9-16.
[3]何克抗.从信息时代的教育与培训看教学设计理论的新发展(下)[J].中国电化教育,1998,12: 9-13.
[4]徐素霞. E-Learning中学习者建模研究[D].武汉:华中师范大学,2007.
[5]史元春.以规矩促发展[N].计算机世界, 2002-07-22(B09).
[6]高鹏.基于数据挖掘的个性化网络教学平台研究[D].西安:西北大学,2005
[7]奚建清,朱斌,陈鹏,张宗杰,文志康.现代远程教育中学习者的相关规范[J].中国远程教育,2002,2:17-19
[8] PeterDolog,NicolaHenze,WolfgangNejdl,et al. Personalization in Distributed E-Learning environments,Proeeedings of the 13th international World Wide Web conference on Alternate track Papers & Posters,2004,5:170-179.
[9]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,2005,4:28-29.
[10]网络教育技术规范(CELTS).[EB/OL].http://www.docin.com/p-10487426.html.
[11]何克抗.建构主义──革新传统教学的理论基础[J].科学课:小学版,2003,12:22-23.
[12]何克抗.建构主义——革新传统教学的理论基础(二)[J].科学课:小学版,2004,1:46-47.
[13] ONASSEND, DAVIDSON M, COLLINS M, et al. Constructivism and computer-mediated communication in distance education [J]. American journal of distance education, 1995, 9(2): 7-26.
[14]模糊逻辑简介.[EB/OL].http://210.40.32.30/gzzy/ArticleShow.asp?ArticleID=1322
[15]张云涛,龚玲.数据挖掘原理与技术[M].北京:电子工业出版社,2004
[16]刘桓,曹红菊.自适应学习系统的研究与设计[J].软件导刊,2006,6:39-41.
[17] Brusilovsky. Adaptive Educational Systems on the World - Wide - Web: A Review of Available Technologies. Proceedings of Workshop "WWW - Based Tutoring" at 4th International Conference on Intelligent Tutoring Systems (ITS'98), San Anto (1998)nio, TX, 08.
[18]余胜泉.适应性学习——远距离教育发展的趋势[J].开放教育研究,2000,3:11-15.
[19] FONSECA F, EGENHOFER M, AGOURIS P, et al. Using ontologies for integrated geographic information systems [J]. Transactions in GIS, 2002, 6(3): 231-57.
[20] A Méndez-Vilas, A Solano, J Mesa and JA Mesa. Current Developments in Technology-Assisted Education, 2006, 1:260-264
[21] Jia B,Zhong SC,Zheng TY,et al. The Study and Design of Adaptive Learning System Based on Fuzzy Set Theory,in press.
[22]汪晓岩,胡庆生,李斌,等.面向Internet的个性化智能信息检索[J].计算机研究与发展,1999,36(9):1039-1046.
[23]李铮,赵桂钦.ICAI系统学习者建模的研究[J].计算机工程与科学,2002,3:101-104.
[24]来兴平,伍永平.采煤学多媒体智能CAI系统的设计与实现[J].计算机系统应用,1997,2:34-35.
[25]周春萍,周相泉.基于贝叶斯网络的自适应学生模型的研究[J].山东轻工业学院学报(自然科学版),2007,4:3-6.
[26]陈庚,安玉洁,李亚春等.远程学习者特征研究的现状[J].《中国远程教育》, 2005,11:31-33.
[27] RM加涅,LJ布里格斯,WW韦杰著皮连生,庞维国等译,教学设计原理[M]华东师范大学出版社,2001.
[28]冯红,王陆,杨卉.多目标的学习者模型研究[J].计算机工程与应用,2003,36:98-100.
[29]刘通江.个性化课件生成系统中动态学生模型的研究[D].北京:首都师范大学,硕士学位论文,2004.
[30]刘艺.智能教学系统中学生模型的构建[J].丹东纺专学报,2005, 1:64-67.
[31]冯锐.关于网络教学中学生特征知识分析的探讨.甘肃广播电视大学学报[J], 2007,17(2):3-6.
[32]李镇西,李广生.莫把谈话作谈心[J].班主任,2003,7:41-42.
[33]李翠云.罗伯特·加涅作为丰碑和旗帜挺立.呼伦贝尔学院学报,2006,4:30-33.
[34] Jia B,Zhong SC,Zheng TY,et al.The Construction and Evolution of Learner Model in Adaptive Learning System[C]. In:Hj. Kamaruzaman Jusoff, eds.Proc. of The 2009 International Conference on Computer Technology and Development (ICCTD 2009),USA:IEEE.2009.148-152.
[35]庄致.自适应远程教学系统中学生认知水平估算方法[J].计算机工程与应用,2007,3:281-284.
[36]唐素勤,钟智.学生认知能力的评估[J].广西科学院学报,2002,4:281-284.
[37]姜曾贺,吴战杰.网络环境下多维学习者特征分析模型的构建[J].电化教育研究,2005, 4:71-73.
[38]吴战杰.网络远程教育中学习者特征分析体系的构建及学生模型的设计[D].陕西师范大学.2004.
[39]赵以涛,杨雪.基于网络教育的学习者特征分析系统的设计与实现[J].中小学电教,2006,12:56-58.
[40]朱斌,文志康.学习者模型标准的研究与应用[J].《计算机工程》,2002,Z1:300-303.
[41]孙志伟.基于学习者特征的个性化学习支持系统的研究[D].天津师范大学.2009.
[42] CLAYPOOL M, LE P, WASED M, et al. Implicit interest indicators[C], F, 2001. ACM New York, NY, USA.
[43]胡运安,吕智慧,吴杰等.基于SCORM的学习行为采集模型的设计与实现[J].计算机工程与应用,2004,33:106-108.
[44]杨卉,王陆.基于网络的个性化学习系统中学习者个性特征的提取算法[J].计算机工程与应用,2003,25:179-181.
[45]赵英姿.基于用户行为模式分析的个性化学习支持系统[J].职业教育研究,2006,6,122-123.
[46]冯锐.网络学习支持系统中学生特征分析模型的构建及技术实现[J].中国电化教育,2006,12:31-33.
[47] NAING M, LIM E, GOH D. Ontology-based Web annotation framework for hyperlink structures [J]. Proceedings of WISE Workshops 2002, 2002, 184-93.
[48] LIU Z, LIU L, KANG H, et al. An Ontology-Based Method of Adaptive Learning, F, 2009 [C].
[49]刘志勇,刘磊,刘萍萍,杨帆,贾冰.一种基于语义网的个性化学习资源推荐算法[J].吉林大学学报工学版增刊,2009,39(2): 391-395.