贝叶斯分类技术在高校教师教学质量评价中的应用  

Application of Bayes classification technology in evaluating university teaching quality

作　　者：孙笑微[1] 

机构地区：[1]沈阳师范大学科信软件学院,沈阳110034

出　　处：《沈阳师范大学学报（自然科学版）》2014年第1期98-102,共5页Journal of Shenyang Normal University:Natural Science Edition

基　　金：辽宁省百千万人才基金资助项目(2011921046);沈阳师范大学教改立项课题(JG2012-YB086)

摘　　要：高校进行教师教学质量评价是提高教师教学质量,确保教育品质的重要手段。然而目前很多高校对教师教学质量的评价主要是给出一个结论,而对影响教师教学质量的主要因素并没有进行分析。根据高校教师教学质量评价中存在的不足和问题,将贝叶斯分类技术应用于高校教师教学质量评价体系中。讨论了贝叶斯分类的定义和方法,介绍了朴素贝叶斯分类器,并给出具体的数据分类实例,利用过去已有的教学质量评价的经验数据进行实验。实验结果表明贝叶斯分类具有较好的分类性能和较高的分类精度,贝叶分类技术用于教师教学质量评价完全可行。通过贝叶斯分类对教师教学质量进行合理评价,克服人为因素对评价结果的直接影响,为以后的教学质量评价提供合理科学的技术支持。In order to improve teaching quality and ensure that the quality of education, colleges and universities implement teaching quality evaluation are an important means. However, in most of universities now, teachers are only given a result for teaching quality valuation, without analyzing the association between teaching quality and teacher stuffs. According to the disadvantages and problems of evaluating university teaching quality, the authors put forwards a method, i.e. , applying Bayes classification technology to evaluate university teaching quality. The definition and methods of Bayes classification are discussed, and the algorithm of Naive Bayes classifier is introduced. The detailed data classification example is also presented, and draw underlying laws with reference to the existing data on experiment. The experimental results show that Bayes classification has perfect classification capability and higher classification accuracy. It is entirely feasible to apply Bayes classification technology to evaluate teaching quality. Applying Bayesian classification on a reasonable assessment of teaching quality can overcome human factors directly affect the results of the evaluation. It can provide reasonable and scientific technical support for the policy-making of the teaching quality evaluation in future.

关 键 词：贝叶斯分类 朴素贝叶斯分类器 教学质量 评价模型 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]