基于隶属等级量化的社区学习者能力综合评价  

Ability Assessment Model in Learning Community Based on a Membership Classification Quantitative

作　　者：程艳[1] 许维胜[2] 何一文[2] 

机构地区：[1]江西师范大学计算机信息工程学院,南昌330022 [2]同济大学电子与信息工程学院,上海201804

出　　处：《计算机科学》2010年第9期234-238,263,共6页Computer Science

基　　金：国家自然科学基金项目(70871091);国家自然科学基金项目(60804042)资助

摘　　要：以学习者为中心的学习评价标准从知识转向了能力。把虚拟学习社区作为E-learning学习的平台,基于虚拟学习社区和E-learning学习的特点,结合个人学习能力、学习协作能力以及成绩考核来对社区学习者能力进行模糊综合评价,建立了社区学习者能力模糊综合评价模型,其评价结果是与评语集相对应的隶属度向量。为了解决评价结果模糊度较大的问题,充分利用了综合评判带来的信息,提出并建立了隶属度向量等级量化模型,并对评价结果作进一步量化,达到了进一步准确区分学习者能力的目的。The assessment standard of the learner-centered teaching evaluation steers from knowledge to ability.Using virtual learning communities as a E-learning platform,a community learners＇ ability fuzzy assessment model was set up,based on the characteristics of virtual learning communities and E-learning,combining personal ability,online coo-peration ability and the test results.The assessment agrees with the membership vector of the comments.To narrow the fuzzy disparity,this paper made use of the information from the comprehensive evaluation to build a classification quantitative model,thus further quantifying the assessment to classify the students＇ ability more accurately.

关 键 词：能力评估 隶属度向量 等级量化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]