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基于多源信息融合的本科生综合素质评价研究
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摘要
随着高等教育进入大众化,全球化,价值多元化时代,如何评价专业不同、禀赋各异的本科生的素质,是一个复杂的问题。仅凭个人的精力、知识、经验和智慧已无法掌握所有必要的与本科生素质相关的知识和信息来做出合理的评价。评价者在评价时需要综合多种来源的信息,由多位专家以及与本科生培养过程中密切相关的人员组成评价群体进行评价,依靠群体的智慧、信息和知识来解决问题。由于受到评价者知识结构、评判水平和个人偏好等主观因素及本科生综合素质本身的模糊性、不确定性和复杂性的影响,评价信息具有模糊性和不确定性。
     本科生综合素质评价面临的主要问题包括:第一,评价指标的确定及评价主体单一的问题。不管评价的对象是一年级新生还是高年级本科生或者毕业生,不管评价主体是教师、辅导员、管理人员还是校外人员,评价指标没有区分,指标权重没有区分,因而评价结果不符合本科生综合素质的个性化评价要求;第二,评价过程是静态的,不能考虑本科生的成长过程,对本科生的多次评价没有反馈,因而无法体现本科生的成长历程,更无法提出针对性的激励措施。第三,评价信息来源单一,评价结果无法真实反映本科生的综合素质水平。
     针对以上问题,本文在考察了现有本科生综合素质评价系统的基础上,提出了本科生综合素质评价框架结构,进一步运用信息融合理论、Agent技术等研究综合评价过程中的多源数据获取、数据融合、评价指标及权重、个性化综合评价模型,形成了本科生综合素质评价的完整理论体系,为高校进行本科生综合素质管理提供理论支撑,所得到的重要结论对引导高校个性化素质教育、提高高校素质评价与管理水平具有较强的实践指导意义。
     论文的研究内容如下:
     一、通过对本科生综合素质评价目标、评价方法、评价指标的文献综述,结合高校本科生综合素质评价管理的现状,分析现有评价体系中存在的问题,提出评价人才的标准有多种类型、多种规格、多种层次,避免千人一面,充分发掘本科生潜能,主张多元评价主体和多元价值评价理念。
     二、提出建立个性化、动态的综合素质评价体系,明确针对不同评价主体、不同评价对象进行个性化定制评价的必要性和可行性。进一步从模型、应用和实施三个维度建立了本科生综合素质评价的框架结构。第一个维度是模型维度,主要说明论文研究的思路,包括多源信息的分析;多源信息的信息融合方法建立相应的数据库、模型库;通过二元语义融合模型确定评价指标、指标的权重,并进一步建立个性化可定制的评价模型。第二个维度是实施维度,采用多Agent技术,建立包括信息Agent、信息融合Agent、评价Agent、管理Agent和界面Agent的多Agent系统,对个性化评价过程进行模拟。第三个维度是应用维度,主要考虑应用的主体、客体(对象),对不同的主客体可以进行不同评价模式的定制。
     三、本科生综合素质评价的数据来源是多源异构的,既有来自于各类不同人员的知识,又有来自于不同信息系统的数据信息;评价方法是多样的。因而采用多源信息融合方法将多源数据、多种方法进行综合建立信息融合数据库、模型库等,为评价提供信息基础和技术支持。
     四、在本科生综合素质评价的研究中,出于本科生综合素质评价过程中有部分信息具有主观性和模糊性的特点,为了避免信息损失,首先将客观评价、主观评价等评价信息进行标准化处理,为进一步的数据分析提供有效的目标数据;然后借助二元语义方法、信息融合算子进行群体评价信息的集结;最后计算得出了综合评价的指标权重。
     五、建立了可定制的本科生综合素质评价模型,并详细阐述了个性化评价指标的选取及个性化评价过程。对本科生综合素质进行动态的和个性化的评价,避免了千人一面、千篇一律的评价,体现了以本科生为中心的个性化评价的思想。
     本文的创新性体现在以下三个方面:
     一、重视本科生个性、以人为本的理念,将多源信息融合理论和多Agent技术引入到本科生综合素质评价研究中,建立了模型维度、应用维度和实施维度的三维立体的本科生综合素质评价框架结构,为本科生综合素质评价体系的建立提供了思路。
     二、采用信息融合方法将多源数据、多种评价方法进行综合,并采用多元信息融合算子和二元语义方法给出了综合素质评价的专家群体评价意见,并确定了综合评价的指标权重,为综合评价提供了理论依据。
     三、考虑不同的评价主体和评价对象,建立了个性化的可定制评价模型,针对不同类别的本科生培养的不同阶段和不同的评价目标,用不同的评价模型、评价准则来进行评价。该评价模型不仅可以对本科生的全面素质培养起到导航作用,也使高校的素质教育和管理工作更具针对性,主动性和实效性。
It is a complicated problem to evaluate the quality of the undergraduates according to their different majors and characteristics when higher education is becoming popular, globalized and value-diversified. It is unable to master all the necessary and relevant knowledge or information to evaluate the quality, and make a reasonable evaluation depending on personal energy, knowledge, experience and wisdom. Evaluators have to integrate multi-source information in the procedure of evaluating, from experts as well as undergraduates training process is closely related to the composition of the evaluation group to evaluate the wisdom of relying on groups, information and knowledge to solve problems. Evaluators have to deal with information from different sources. It was used to evaluate knowledge of the structure due to the evaluators, judging the level and personal preferences and other subjective factors and the overall quality of undergraduates by the evaluation group which made of experts and relevant personnel closely to undergraduates training.
     The Main problems on evaluating the comprehensive quality of the undergraduates were divided into three aspects. Firstly, the problem of establishing stable evaluation index system and the singleness of evaluation objects. Whether the object of evaluation is a freshman, upperclassman or graduates, regardless of evaluation of the main teachers, counselors, administrators or school personnel, there is no distinction for index indicators and therefore not suited to evaluate the result of quality to personalized evaluation requirements. Secondly, the evaluation process is static and their growth process was not considered, and no feedback is given for the result of the evaluation. So the result could not reflect the growth process of the undergraduates and it's hard to put forward the pertinent incentive policies. Thirdly, the evaluation result is too simple to reflect of the true level of quality of students.
     Given the above problems, after examined the existing undergraduates" comprehensive evaluation system, the paper proposed the framework for Comprehensive Evaluation of Undergraduates, furthermore. Information Fusion Theory. Agent Technology were also used in the evaluation process of comprehensive multi-source data acquisition, data fusion, assessment index and weight, personalized comprehensive evaluation model were made of the complete theoretical system for comprehensive evaluation for undergraduates'quality, which provided theoretical support. Important conclusions were used to guide the university personal qualities education and improve the quality of evaluation and management with strong practical significance. The main contents of the paper are as follows:
     Firstly, existed evaluation system problems were analyzed on the quality of undergraduate's through the evaluation objectives, evaluation methods and the literature review of evaluation index, combined with the status of evaluation management of the quality of university undergraduates, it was pointed out that evaluation criteria for a variety of types of talent, a variety of specifications, a variety of levels, was to avoid using the same one for thousands of students, to fully exploit the potential quality of students, and appraised subject pluralism, appraised in contents and appraise method variety.
     Secondly, the paper proposed the establishment of personalized, dynamic and comprehensive quality assessment system, a clear evaluation of different subject, different evaluation objects to customize the necessity and feasibility evaluation. Furthermore a framework was built for comprehensive evaluation from the model, application and implementation of the three dimensions of undergraduates. The first dimension is the model dimension, the main idea of that thesis, including the analysis of multi-source data source; multi-source data fusion method to establish the corresponding database, model base; determined by binary semantic fusion model assessment index, index weight, and further establish the evaluation model customization. The second dimension is the implementation of the dimension. multi-Agent technology, the establishment of multi-Agent system including Information Agent, Information Fusion Agent. Evaluation Agent, Management Agent and Multi-Agent System Interface Agent, individualized evaluation process simulation. The third dimension is the application of the dimension, mainly considering the application of the subject and object. The main object of different evaluation models can be customized for different objects.
     Thirdly, considered the quality of the comprehensive evaluation of the data source is multi-source heterogeneous, both from the knowledge of all kinds of different people, but also from different information systems data; evaluation method is diverse. Thus a multi-source information fusion method was used on multi-source data, a variety of methods to establish a comprehensive database of information fusion, model base, provided information infrastructure for the evaluation.
     Fourth, in the study on the quality of evaluation of the undergraduates, considered a lot of subjective quality assessment information, fuzzy information, it were avoided to loss of information, first objective evaluation, subjective evaluation of standardized evaluation of information for further data analysis were a valid target data; and then 2-tuple linguistic representation, information fusion operator were used for the evaluation of the quality of the views of experts on group decision making; the paper calculated a comprehensive evaluation of the index weight at last.
     Fifthly, a customized evaluation model on the quality of students was made, so the detailed evaluation of the individual and the individual evaluation of the selection process were described. The unbalanced, unified assessment was avoided and the student-centered evaluation based on personalized ideas was reflected for using dynamic quality of undergraduate and personalized evaluation.
     The innovations were reflected in the following three aspects:
     Firstly. the emphasis on student's personality, people-oriented concept, the introduction of the theory of Multi-source Information Fusion and Multi-agent Technology into the Comprehensive Evaluation of the quality of undergraduates, the establishment of the model dimension, the application of three-dimensional dimensions and implementation of the dimension framework for Comprehensive Evaluation of undergraduates, which provided a guideline to establish comprehensive quality evaluation system.
     Secondly, a comprehensive evaluation of the expert group decision quality advice and a comprehensive evaluation system to determine the index weight was given to the usage of information fusion methods to multi-source data while a comprehensive variety of evaluation methods and usage of multiple information fusion operator and 2-tuple linguistic representation method, which provided a theoretical basis for evaluation.
     Thirdly, considered the different evaluation of the main objects, the establishment of a personalized evaluation model tailored was used for different types of education of undergraduates at different stages and different evaluation objectives, with different evaluation models, evaluation criteria to be evaluated. The evaluation model was not only used for the quality of undergraduates navigation training, but also for the quality of university education and more focused management, which would be more proactive and effective.
引文
[1]国家中长期教育改革和发展规划纲要(2010-2020年).
    [2]Gronlund, N.E., The use of dual grouping in student-centered teaching. Journal of Educational Psychology,1955.46(1):1-16.
    [3]杨六栓,中国加入WTO后本科生综合素质培养.经济师,2003(5):88-111.
    [4]Charlton, B.G. and P. Andras, Globalization in science education:An inevitable and beneficial trend. Medical Hypotheses,2006.66(5):869-873.
    [5]霍丽荣,云计算环境下的多元化学生评价研究,2010,上海师范大学.
    [6]刘敏,钟志贤,基于教育博客的本科生自主学习.远程教育杂志,2007(4):56-59.
    [7]祁园园.多元智能评价观对学生评价的启示.继续教育研究,2008(8):156-157.
    [8]杨保安,多目标优化决策方法的研究方问探讨——走向智能化[J].西北工业大学学报,1990(4):472-477.
    [9]杨保安,张世杰,李先国,智能型、交互式目标规划模型决策系统的研究[J].西北工业大学学报,1993(2):163-167.
    [10]HOSSEINIAN S S, NAVIDI H, HAJFATHALIHA A. A new linear programming method for weights generation and group decision making in the analytic hierarchy process [J]. Group Decision and Negotiation,2009 (11):1572-1607.
    [11]徐景良,B/S模式综合评价支持系统研究,2006,大连理工大学.
    [12]周远清,素质·素质教育·文化素质教育——关于高等教育思想观念改革的再思考[J].清华大学教育研究,2000(3):1-4.
    [13]戴安.弗古森等著,王玲玲译.个性化学习设计指南[M].华东师范大学出版社,2009.
    [14]杨季美,史本山,群体评价中的并合方法.系统工程理论与实践,1992(1):49-51,13.
    [15]陈骥,群组评价技术研究,浙江工商大学硕士论文.2006.
    [16]叶帆,洪振杰.不完全信息群体决策专家权重的集结.应用数学与计算数学学报,2006,20(1):63-67.
    [17]杨雷,席酉民.群体讨论对个体偏好极端性转移的影响.系统工程,1997,15(1):9-13
    [18]彭怡,胡杨,郭耀煌.基于群体理想解的多属性群决策算法.西南交通大学学报,2003,38(6):682-685.
    [19]Herrera F, Verdegay J L. Linguistic assessments in group decision. Proceeding of 1st European Congress on Fuzzy and Intelligent Technologies. Aachen,1993,941-948.
    [20]牟琼,吴庆军,鲁成国.一种考虑多个指标的模糊数排序.广西师范学院学报,2004(6):17-21.
    [21]江文奇.群决策的一致性寻求方法.系统工程与电子技术[J].2007,29(5):756-758.
    [22]周洁,李德敏,张友良.群决策一致性寻求方法与算法[J].系统工程理论与实践,1999,(6):80-84.
    [23]胡应平.基于模糊语言群体决策的一致性协调技术[J].系统工程学报,2000,15(2):148-152.
    [24]王宗军.面向复杂对象系统的集成式智能化评价支持系统开发环境的设计与实现.系统工程学报,1995,10(1):90-96.
    [25]王宗军,面向复杂对象系统的多人多层次多目标综合评价问题的形式化研究.系统工程学报,1996,11(1):1-9.
    [26]王宗军,基于知识的综合评价问题的模糊推理求解方法,系统工程学报,1998(1):1-11
    [27]NWANA H S. Software agents:an overview.Knowledge Engineering Review,1996, 11(3):46-50.
    [28]裴开俊,朱明富,多目标群体评价方案生成支持系统,2000:中国云南昆明,中国控制与决策学术年会论文集.
    [29]Richard M. Adler. Distributed coordination models for client/server computing. IEEE Computer,1995,14-22.
    [30]Shin, J. C., & Harman, G. New Challenges for Higher Education: Global and Asia-Pacific perspectives. Asia Pacific Education Review,2009,10(1):1-13.
    [31]O'Reilly, M & Morgan,, On-line assessment: creating communities and opportunities, in Computer-assisted assessment in higher education, eds S Brown, P Race & J Bull, Kogan Page, Birmingham,1999:149-161.
    [32]Kautz H., B. Selman, M. Coen (1994), Bottom-up Design of Software Agents. Communi-cations of the ACM,1994,37(7):143-146.
    [33]Hayes-Roth B., An Architecture for Adaptive Intelligent Systems, Artificial Intelligence: Special Issue on Agents and Interactivity,1995(72):329-365.
    [34]Benyon, D. and D. Murray, Adaptive systems:from intelligent tutoring to autonomous agents. Knowledge-Based Systems,1993,6(4):197-219.
    [35]Lejter, M., and T. Dean, A Framework for the Development of Multiagent Architectures, IEEE Computer Society Press,1996,11(6):47-59.
    [36]O'Hare, G.M.P. and A.W.J. Chisholm, Distributed Artificial Intelligence:An Invaluable Technique for the Development of Intelligent Manufacturing Systems. CIRP Annals-Manufacturing Technology,1990.39(1):485-488.
    [37]M. Wooldridge. Agent-Based Software Engineering. IEEE Proc. Softw. Eng.1997,144(1): 26-37.
    [38]Nicholas R. Jennings, Katia Sycara, Michael Wooldridge. A roadmap of agent research and development. Autonomous Agents and Multi-Agent Systems.1998 (1):7-38.
    [39]Nicholas R. Jennings. On Agent-Based Software Engineering. Artificial Intelligence.2000, 117:277-296.
    [40]T Finin, R Fritzson, D Mckav et al. KQML as an Agent Communication Language [C]. In: Proceedings CIKM'94,1994:27-61.
    [41]刘占伟,邓四二,滕弘飞.复杂工程系统设计方案评价方法综述[J].系统工程与电子技术,2003(12):1488-1491.
    [42]Fleming, J.S. and W.A. Watts, The dimensionality of self-esteem:Some results of a college sample. Journal of Personality and Social Psychology,1980.39(5):921-929.
    [43]Herrera F, Herrera-Viedma E, Martinez L. A fusion approach for managing multi-granularity linguistic terms sets in decision making [J]. Fuzzy Sets and Systems,2000,114 (1):43-58.
    [44]Herrera F, Martinez L Sanchez. Managing non-homogeneous information in group decision making [J].European J of Operational Research,2005,166(11):115-132.
    [45]张园林,匡兴华,一种基于多粒度语言偏好矩阵的多属性群决策方法[J].控制与决策,2008,23(11):1296-1300.
    [46]Herrera, F., E. Herrera-Viedma and J.L. Verdegay, A sequential selection process in group decision making with a linguistic assessment approach [J]. Information Sciences,1995,85(4): 223-239.
    [47]Ma J, Fan Z B, Huang L H. A subjective and objective integrated approach to determine attribute weights. European Journal of Operational Research,1999(112):397-404.
    [48]俞立平,潘云涛,武夷山,科技教育评价中主客观赋权方法比较研究.科研管理,2009(4):154-161.
    [49]冯珊.多目标综合评价的指标体系,系统工程与电子技术,1994(6):17-24.
    [50]王浣尘,吴健中,王鹤祥.特尔斐法在设计港址评价指标体系中的应用.系统工程理论与实践,1985,(1):22-26.
    [51]苏为华,统计指标理论与方法研究,北京:中国物价出版社,1998.
    [52]叶义成,柯即华,黄德一育.系统综合评价技术及其应用,北京:冶金工业出版社,2006.
    [53]田志友,奚俊芳,王浣尘.社会经济系统评价指标体系设计:方法论原理及其实现—以产业集群竞争力评价为例.系统工程理论与实践,2005(11):1-6.
    [54]柴小青.应用解释性结构模型建立评价指标体系的递阶结构.中国管理科学,1997,5(4):60-64.
    [55]董玉成,陈义华,王双.递阶层次结构决策指标体系构建算法及应用.控制与决策,2005,20(4):403-407.
    [56]胡永宏,贺思辉.综合评价方法[M].北京:科学出版社,2000.
    [57]李随成,陈敬东,赵海刚定性决策指标体系评价研究.系统工程理论与实践,2001,(9):22-28.
    [58]王璐,包革军,王雪峰.综合评价中的一种新的指标选择方法.数理统计与管理,2004,23(1):72-76.
    [59]瞿堡奎主编,陈玉琨、赵永年选编.教育学文集.教育评价[C].北京:人民教育出版社,1989.
    [60]Dolan, R.C. and R.M. Schmidt, Modeling institutional production of higher education. Economics of Education Review,1994.13(3):197-213.
    [61]W.M. Aikin. The story of eight year study [M]. Harper & Row,1942.
    [62]Fresko, Barbara; Nasser, Fadia. Interpreting student ratings:consultation, instructional modification, and attitudes towards course evaluation. Studies in Educational Evaluation,2001, 36(4):291-305.
    [63]斯塔弗尔比姆(Stufflebeam. D. L.)等著,苏锦丽等译.评估模型[M].北京:北京师范大学出版社,2007:26-29.
    [64]Lincoln, Y.S.Fourth Generation Evaluation in the New Millennium In S.I. Donaldson & M. Seriven(Eds.), Evaluating social programs and problems:visions for the new millennium. Mahwah, N.J:Lawrence Erlbaum..
    [65]Tamura S, Higuchi S, fanaka K. Pattern classification based on fuzzy relations. IEEE SMC, 1971, 1(1):217-242.
    [66]沈志莉.发展性高等教育评价研究[D].华中师范大学,2003.
    [67]俎媛媛,真实性学生评价研究[D],华东师范大学,2007.
    [68]Ellen Weber. Student Assessment That Works:A Practical Approach [M]. Boston:Allyn and Bacon,2002.
    [69]Benjamin, L.&Lomofsky, L. Effects of the observation of dynamic and static assessment on teachers' perceptions of the learning potential of less academic learners [J], Journal of Cognitive Education and Psychology,2002,2(2):102-123.
    [70]Julian G. Elliott, Dynamic Assessment In Educational Contexts:Purpose and promise, IN C.S.Lidz &J.G Elliottt (Eds) Dynamic Assessment:prevailing models and applications, New York. Elsevier Science Inc,2000(6):713-740.
    [71]Bellanca, J.M. Chapman, C. and Swartz, E.《多元智能与多元评价——运用评价促进学生发展》.北京:中国轻工业出版社,2004.
    [72]Glenn Finger, Neil Russell.School Evaluation Using Fourth Generation Evaluation:A Case Study [J]. Evaluation Journal of Australasia,1994,6(1):43-54.
    [73]Huebner, Angela.1. A constructivist approach to evaluation methodology:Implications for positive youth development [D]. The University of Arizona,1995.
    [74]Patton, Michael Quinn. Qualitative research & evaluation methods. Thousand Oaks Calif. Sage Publications,2002.
    [75]Tom O'Neill. Implementation Frailties of Guba and Lincoln's Fourth Generation Evaluation Theory [J]. Studies in Educational Evaluation,1995(21):5-21.
    [76]Neil Russell and John Willinsky.Fourth Generation Education Evaluation:The Impact of A Post-modern Paradigm on School BasedEvaluation, Studies in Educational Evaluation,1997, 23(3):187-199.
    [77]Richard Laughlin and Jane Broadben. Redesigning Fourth generation Evaluation:An Evaluation Model for the Public-sector Reforms in the UK [J].Evaluation,1996(2):431-451.
    [78]James L.Heap. Constructionism in the Rhetoric and Practice of Fourth Generation Evaluation [J].Evaluation and Program Planning,1995,18(1):51-61.
    [79]Angela J.Huebner and Sherry C.Betts.Examining Fourth Generation Evaluation:Application to Positive Youth Development [J]., Evaluation.1999(5):340-358.
    [80]Gardner, H 1993b,'Introduction to the Second Edition', in Frames of mind:The theory of multiple intelligences, ed. H Gardner, Fontana, London.
    [81]Gardner, H, Multiple intelligences:The theory in practice, Basic Books, New York,1993d.
    [82]Gardner, H, Reflections on multiple intelligences [J], Phi Delta Kappan,1995,77(3):200-208.
    [83]Phillips, W.M., Peterson, G.D., and Aberle, K.B., Quality Assurance for Engineering Education in a Changing World [J], International Journal of Engineering Education,2000,16(2): 97-103.
    [84]McGourty J., Sebastian C., Swart, W., Performance Measurement and Continuous Improvement of Undergraduate Engineering Education Systems, Proceedings of the 27th Frontiers in Education Conference, Pittsburgh, PA,1997,1294-1301.
    [85]Sternberg, R. Intelligence Applied:Understanding and Increasing Your Intellectual Skills [M]. San Diego, CA:Harcourt Brace Jovanovich,1986.
    [86]Lee, S.W. and C. Tsai, Students' perceptions of collaboration, self-regulated learning, and information seeking in the context of Internet-based learning and traditional learning [J].. Computers in Human Behavior,2011,27(2):905-914.
    [87]陈衍泰,陈国宏,李美娟.综合评价方法分类及研究进展[J].管理科学学报,2004(4):69-79.
    [88]刘军红,刘恩霄,基于模糊理论的本科生综合素质评价方法研究[J].河北农业大学学报(农林教育版),2007(3):22-24,28.
    [89]王桂芳,基于人工智能的大学生综合素质评价研究,2010,硕士学位论文,北京服装学院.
    [90]刘威,高校本科生综合素质评价体系的研究[J],2004,硕士学位论文,华北电力大学(北京)
    [91]谭旭红,大学生素质测评系统设计与实施[J].黑龙江科技学院学报,2002(1):55-58.
    [92]谭旭红,张庆华,高校全程性考试评价体系的建立[J].黑龙江高教研究,2004(3):90-92.
    [93]张宏伟等,本科生综合素质评价研究[J].天津大学学报(社会科学版),1999(2):95-98.
    [94]朱建军,梁时间,本科生综合素质评价改革研究[J].中国校外教育,2010(18):5.
    [95]张业成,本科生素质综合测评初探[J].十堰大学学报,1992(4):17-23.
    [96]张琼,试述本科生素质综合测评[J].惠州学院学报(社会科学版),2004(1):79-83.
    [97]许二平,姬旺华,对高校现行的大学生综合测评制度的调查分析[J].河南中医学院学报,2005(1):67-68,76.
    [98]万远英,尹德志.本科生综合素质层次分析评价体系及其数学模型[J].西南民族大学学报(人文社科版),2003(12):191-193.
    [99]张富程,谢爽,吴应刚.本科生综合素质量化评优模型的构建[J].成都理工大学学报(社会科学版),2007(12):87-91.
    [100]Saaty T L. The Analytic Hierarchy Process [M]. New York: McGraw Hill,1980.
    [101]Saaty, T.L. Multicriteria Decision Making: The Analytic Hierarchy Process, RWS Publica-tions, Pittsburgh, PA,1990.
    [102]毛军权,大学生综合素质评价系统的设计与评价方法的研究[J].上海理工大学学报(社会科学版),2002(2):第10-13页.
    [103]任泰明.评价本科生综合素质的AHP-FUZZY-T模型[J].兰州石化职业技术学院学报,2005,5(4):35-37.
    [104]俞守华,董绍娴,区晶莹等.基于方法集的本科生综合素质评价[J].高等农业教育,2008(2):84-88.
    [105]蒋娜,赵甫.模糊综合评判在本科生综合素质测评中的应用[J].科技信息(学术版),2008(2):112-113.
    [106]张建军.本科生综合素质的模糊综合评价[J].青岛理工大学学报,2008(1):103-106.
    [107]乌力更.本科生综合素质评价体系的构建与应用[J].内蒙古工业大学学报(社会科学版),2002(2):98-101.
    [108]张英,冯艳芳.基于模糊层次分析法的本科生综合素质评价[J].武汉理工大学学报(社会科学版),2007,20(5):707-710.
    [109]卢铁光,王立,汪志君.本科生综合素质评价方法-模糊综合评估法[J].高等农业教育,2002,132(6):86-57.
    [110]周人民.本科生综合素质模糊综合评价[J].怀化医专学报,2003(2):95-96.
    [111]谢昌浩.对高校学生评价指标体系主成分分析[J].云南财经大学学报,2004(4):113-117.
    [112]张翎.主成分分析法在高校学生综合素质评价中的应用[J].云南民族学院学报(自然科学),2001,10(1):283-286.
    [113]刘坚,苏军.因子分析在综合素质评价中的应用[J].华东交通大学学报,2004(10):145-149.
    [114]俞立平,一种新的科教组合评价方法——共性数据排序选择模型.统计研究,2009(7):103-108.
    [115]邓聚龙.灰理论基础[M].武汉:华中科技大学出版社,2002.
    [116]Zhang J J,Wu D S,Olson D L. The method of grey related a-nalysis to multiple attribute decision making problems with interval numbers[J]. Mathematical and Computer Modeling, 2005(42):991-998.
    [117]美瑛.用定量分析方法综合评价本科生素质[J].内蒙古师大学报(哲学社会科学版),1999(8):88-90.
    [118]张士林,刘美多,荣河海,刘伟锋.本科生素质教育灰色评价系统研究[J].黑龙江生态工程职业学院学报,2004(10):145-249.
    [119]梁文慧,毕守东,戴照力.本科生诚信品质评价体系及评估模型的构建[J].中国高教研究,2006(5):75-76.
    [120]王殿海,杜丽华.综合评价本科生的方法研究[J].数理统计与管理,1996,15(4):30-34.
    [121]李世锋等,本科生素质教育的动态评价与量化分析[J].武汉工业学院学报,2000(2):88-91.
    [122]刘冬元,唐志刚,姜琴.本科生成绩的统计分析[J].数理医药学杂志,2005(2):140-141.
    [123]Heffernan, T. and C.S. Richards, Self-control of study behavior:Identification and evaluation of natural methods [J], Journal of Counseling Psychology,1981,28(4):361-364.
    [124]Barnette Jr., W.L., Feedback from bachelor of arts psychology graduates. American Psychologist [J].1961,16(4):184-188.
    [125]Zadeh, L. A., Fuzzy Sets [J], Information and Control,1965(8):338-353.
    [126]杜瑛,协商与共识:提高评价效用的现实选择——基于第四代评价实践的分析.教育发展研究,2010(17):47-51.
    [127]杜瑛,我国高等教育评价的范式转换及其协商机制研究,2010,博士论文、华东师范大学.
    [128]Scheerens, J., School Effectiveness Research and the Development of Process Indicators of School funding [J]. School Effectiveness and School Improvement.1990,1(1):61-80.
    [129]吴钢,李勤.学生学习成绩评价的一种理论和方法[J].上海教育科研,1994(6):36-38.
    [130]张宝歌,高等学校学生质量评价体系的研究[J].黑龙江高教研究,2007(12):69-71.
    [131]陈晓云,赵世奎.社会需求——高等教育质量的外在需求[J].现代管理科学,2003(5):89-90.
    [132]Johnson, J.G., Associations Between Family Relationships and Psychiatric Symptomatology in Undergraduate Students [J]. Journal of College Student Psychotherapy,1993(3).
    [133]赵燕,“百名教授学者看大学生素质教育”问卷调查分析[J].南京医科大学学报(社会科学版),2005(2):149-151.
    [134]叶澜.试论当代中国教育价值取向之偏差[J].教育研究,1989(8):28-32.
    [135]阎淳冰,张炳成,素质教育中的教育价值取向探析[J].兰州大学学报,2000(28):47-49.
    [136]徐红,董泽芳,中国高等教育价值取向60年嬗变:教育政策的视角[J].中国高教研究,2010(5):7-10.
    [137]张晓青,论孔子“学而优则仕”的教育价值取向.衡水学院学报,2006(3):10一13.
    [138]扈中平.教育目的中个人本位论与社会本位论的对立与历史统一[J].华南师范大学学报:社会科学版,2000(2):87-94.
    [139]涂可国.论儒学的社会本位与个人本位悖论及其影响[J].哲学研究,2005(1):31-38.
    [140]刘志春.浅析教育价值取向与教育评价.河南师范大学学报(哲学社会科学版),2001(1):97-99.
    [141]李海林,大学生综合素质评价体系与评价方法研究,2008,硕士论文,中国石油大学.
    [142]杨叔子,人文教育:情感、责任感、价值观.南京邮电学院学报(社会科学版),1999(1):1-4.
    [143]杨叔子,继承传统,面向未来,加强人文素质教育[J].高等工程教育研究,1995(4):1-6.
    [144]郁文贤,雍少为,郭桂蓉.多传感器信息融合技术评述.国防科技大学学报,1994,16(3):1-11.
    [145]Hall D L, Linas J. An introduction to multi-sensor data fusion [J]. Proc. IEEE,1997,85(1): 1-23.
    [146]罗贺,多Agent信息融合与协商及其在故障诊断中的应用研究,2009,合肥工业大学,博士学位论文.
    [147]杨善林,罗贺,面向主体的多源信息融合系统建模研究.信息系统学报,2007(1):92-101.
    [148]Rokeach, M., Long-term value changes initiated by computer feedback [J]. Journal of Personality and Social Psychology,1975.32(3):467-476.
    [149]Ting-Peng Liang, Jin-Shiang Huang, A framework for applying intelligent agents to support electronic trading [J], Decision Support Systems,2000,28(4):305-317.
    [150]J H Holland. Adaptation in Natural and Artificial Systems [M], MIT Press,1975:1-20.
    [151]Sarit Kraus. Negotiation and Cooperation in Multi-agent Environments [J], Artificial Intelligence,1997(94):79-97.
    [152]陈富赞等,面向对象模型管理方法的研究及应用.系统工程理论与实践,1999(6):9-15,28.
    [153]高长元.基于Internet高新技术产品评价群决策支持系统研究[D].哈尔滨工程大学,2002.
    [154]高长元,王要武,高新技术产品认定与评价群决策支持系统设计.哈尔滨理工大学学报,2008(5):83-86.
    [155]李德清,李洪兴.状态变权向量的性质与构造[J].北京师范大学学报(自然科学版),2002,38(4):455-461.
    [156]徐则中,一种新的变权向量及其应用[J].数学的实践与认识,2008,38(20):134-138.
    [157]Karake, Z.A., Enhancing the learning process with expert systems [J]. Computers & Education,1990.14(6):495-503.
    [158]刘涛,基于专家系统的人才评价系统研究与实现,2005,硕士学位论文,山东科技大学.
    [159]Yager R R. Non-numeric multi-criteria multi-person decision making [J], Group Decision and Negotiation,1993 (2):81-93.
    [160]Yager R R. Families of OWA operators [J], Fuzzy Sets and Systems,1993b (59):125-148.
    [161]Yager R R. A general approach to criteria aggregation using fuzzy measures [J], International Journal of Man-Machine Studies,1993c (38):187-213.
    [162]Degani R, Bortolan G. The problem of linguistic approximation in clinical decision making [J], International Journal of Approximate Reasoning,1988(2):143-162
    [163]Delgado M, Verdegay J L, Vila M A. Linguistic decision-making models [J], Journal of Intelligent Systems,1992(7):479-492.
    [164]Zadeh L A. The concept of a linguistic variable and its applications to approximate reasoning (Part I). Information Science,1975a(8):199-249.
    [165]Tong M, Bonissone P P.A linguistic approach to decision making with fuzzy sets. IEEE Transactions on Systems, Man and Cybernetics,1980 (10):716-723.
    [166]Zadeh L A. The concept of a linguistic variable and its applications to approximate reasoning(Part II). Information Science,1975b(8):301-357.
    [167]Carlsson C, Fuller R.On fuzzy screening systems. Proceeding 3rd European Congress on Intelligent Technologies and Soft Computing, Aachen,1995:1261-1264.
    [168]Delgado M, Verdegay J L, Vila M A. On aggregation operations of linguistic labels [J]. International Journal of Intelligent Systems,1993(8):351-370.
    [169]Herrera F, Herrera-Vedma E. Aggregation operators for linguistic weighted information. IEEE transactions on Systems, Man, and Cybernetics-Part A:Systerms and Humans,1997,27(5): 646-656.
    [170]Herrera F, Herrera-Viedma E, Verdegay J L. On dominance degrees in group decision making with linguistic preferences.4th International workshop Current Issues in Fuzzy Technologies, CIFT'94, Trento, Italy,1994,113-117.
    [171]Herrera F, Herrera-Viedma E, Verdegay J L. A sequential selection process in group decision making with a linguistic assessment approach. In formation Sciences,1995(85):223-239.
    [172]Herrera F,Herrera-Viedma E, Verdegay J L.Approaching group decision making under linguistic assessments.5th International Workshop Current Issues in Fuzzy Technologies, CIFT95,Trento,Italy,1995 c,205-208.
    [173]Herrera F, Herrera-Viedma E, Verdegay J L. A linguistic decision process in group decision making [J] Group Decision and Negotiation,1996a (5):165-176.
    [174]Herrera F,Herrera-Viedma E,Verdegay J L.Direct approach possessing group decision making using linguistic OWA operators [J], Fuzzy Sets and Systems,1996b (79):175-190.
    [175]Herrera F, Herrera Viedma E, Verdegay J L. Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making [J], International Journal of Approximate Reasoning,1997b (16):309-334.
    [176]Herrera F, Herrera-Viedrria E, Verdegay J L. Choice processes for non-homogeneous group decision making in linguistic setting [J], Fuzzy Sets and Systems,1998 (94):287-308.
    [177]Herrera F, Lopez E, Mendana C, et .al. A linguistic decision model for personnel managements solved with a linguistic biobjective genetic algorithm [J], Fuzzy Sets and Systems, 2001 (118):47-64.
    [178]Torra V The weighted OWA operator [J], International Journal of Intelligent Systems, 1997(12):153-166.
    [179]Yager R R. Application and extensions of OWA aggregation [J], International Journal of Man-Machine Studies,1992a (37):103-132.
    [180]Yager R R.On the inclusion of importance in multi-criteria decision making in fuzzy set frame work [J], International Journal of Expert Systems,1992b(5):211-228.
    [181]Yager R R. OWA neurons:a new class of fuzzy neurons. Proceeding of International Joint Conference On Neural Net works, Vol.Ⅰ, Baltimore,1992d (1):226-231.
    [182]Herrera F, Martinez L.A 2-tuple fuzzy linguistic representation model based on a symbolic translation. Proceeding of Eurofuse-SIC'99 Conference, Budapest,1999a,25-28.
    [183]Herrera F, Martinez L. A selection method based on the 2-tuple linguistic representation model for decision-making with multi-granularity linguistic information. Proceeding EUSFLAT ESTLYF Joint Conference 99, Spain,1999b,453-456.
    [184]Herrera F, Martinez L. A 2-tuple fuzzy linguistic representation model for computing with words [J]. IEEE Transactions on Fuzzy Systems,2000a,8(6):746-752.
    [185]Herrera F, Herrera-Viedma E, Chiclana F.Multiperson decision making based on multiplicative preference relations [J]. European Journal of Operational Research,2001 (129): 372-385.
    [186]Herrera F, Martinez L. A model based on linguistic 2-tuple for dealing with multi granularity hierarchical linguistic contexts in multi-expert decision-making. IEEE Transactions on Systems, Man and Cybernetics-Part B:Cybernetics,2001a,31 (2):227-234.
    [187]CHEN Z F. Consensus in group decision making under linguistic assessment [D]. Manhattan Kansas, Kansas State University,2005.
    [188]BEN-ARIEH D, CHEN Z. Linguisitc group decision making:Opinion aggregation and measures of consenus [J]. Fuzzy Optimization and Decision Making,2006,5 (5):371-386.
    [189]Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units [J]. European Journal of Operational Research,1978(2):429-444
    [190]Chiclana.F, Herrera.F, Herrera-Viedma.E. Integrating three representation Modelsin fuzzy multipurpose decision-making based in fuzzy preference relations[J].Fuzzy Setsand Systems, 1998(97):33-48.
    [191]周晓光,张强.模糊群决策中专家意见的汇总研究[J].北京理工大学学报,2009(10):936-940.
    [192]孙晓东,田澎.群决策中基于一致性强度的专家意见集结方法[J].系统工程与电子技术,2008(10):1895-1898.
    [193]程家瑜.技术预测中咨询专家人数、权重和评价意见的讨论[J].中国科技论坛,2007(5):24-26.
    [194]杨雷.群体决策理论与应用:群体决策中的个体偏好集结方法研究[M].北京:经济科学出版社,2004.
    [195]于春海,樊治平.基于二元语义信息处理的最大树聚类方法[J].系统工程与电子技术,2006,28(10):1519-1522.
    [196]陈岩,樊治平.语言判断矩阵的一致性及相关问题研究.系统工程理论与实践[J].2004,24(4):136-141.
    [197]廖貅武,李恒,董广茂.一种处理语言评价信息的多属性群决策方法[J].系统工程理论与实践,2006,26(9):90-98.
    [198]Chen, Z., D. Ben-Arieh, On the fusion of multi-granularity linguistic label sets in group decision making [J]. Computers & Industrial Engineering,2006,51(3):526-541.
    [199]Xu, Z.. Group decision making based on multiple types of linguistic preference relations[J]. Information Sciences,2008.178(2):452-467.
    [200]姜艳萍,樊治平,具有语言信息的多指标群体综合评价.东北大学学报,2005(7):703-706.
    [201]姜艳萍,樊治平.基于不同粒度语言判断矩阵的群决策方法[J].系统工程学报,2006,21(6):249-253.
    [202]梁昌勇,戚筱雯,张鑫,一种基于不同粒度且属性权重未知的群决策方法.运筹与管理,2010(1):43-48.
    [203]Herrera, F., E. Herrera-Viedma, J.L. Verdegay, A model of consensus in group decision making under linguistic assessments[J]. Fuzzy Sets and Systems,1996.78(1):73-87.
    [204]张细香,方宝红,雷静,等.基于残缺二元语义判断矩阵的群体决策方法[J].东华大学学报:自然科学版,2009,35(1):98-102.
    [205]Herrera F, Martinez L. Computing with words using the 2-tuple linguistic representation model:analysis of consistency and description.8th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU' 2000. Madrid, 2000c,765-772.

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