基于SAWFCM算法的高职院校教学质量评价研究  

Research of Teaching Quality Evaluation of the Higher Vocational College Based on SAWFCM Algorithm

作　　者：任丽娜 Ren Lina(Department of Information Engineering,Guizhou Light Industry Technical College,Guiyang 550001,China)

机构地区：[1]贵州轻工职业技术学院信息工程系,贵阳550001

出　　处：《黑龙江科学》2021年第5期64-65,共2页Heilongjiang Science

基　　金：贵州轻工职业技术学院项目:基于改进聚类算法的高职院校教学质量评价研究(18QY009)。

摘　　要：为客观和准确评价高职院校教学质量,提出了一种基于SAWFCM算法的教学质量评价方法。该方法将教学质量相关影响因素作为特征空间中的样本,每次运行时都以当前数据为依据来进行各个状态的重新划分,更新每个样本的权重,不过高依赖随机选取的初始聚类中心和随机生成的初始隶属矩阵。以贵州轻工职业技术学院为例进行实验分析,论证了评价模型的可行性,但评价体系不全面,算法准确度有待提高,算法不能自动获取聚类数量,下一步需完善基于大数据的教师教学质量评价体系,改进该模糊聚类算法。In order to objectively and accurately evaluate the teaching quality of the higher vocational college,the research proposes a kind of teaching quality evaluation method based on SAWFCM algorithm.In the method,the associated influencing factors of teaching quality are regarded as the samples of characteristic space.They should be redistricted into different positions according to the current data,the weight of each sample be updated,and that the initial clustering center selected randomly and initial subjection matrix generated randomly should not be highly relied on.Through taking Guizhou Light Industry Technical College as an example,the research arguments the feasibility of evaluation model.However,there are problems,i.e.the evaluation system is not comprehensive,the accuracy of algorithm needs improvement,the number of clusters can’t be automatically acquired in the algorithm,and the teaching quality evaluation system based on big data needs further improvement.So the fuzzy clustering algorithm needs improvement.

关 键 词：SAWFCM算法 高职院校 教学质量评价 

分 类 号：G712.4[文化科学—职业技术教育学]