摘要
目的完善原有的考试测量系统中传统统计分析方法,加大对试卷中隐性知识的测量力度和测量效率,为改进高校教育方法和提高教学质量提供依据.方法首先用传统的教育测量方法即基本的统计方法对成绩数据库进行分析,然后结合支持向量机理论进行进一步的分析.结果结合支持向量机的考试测量分析结果比传统的仅用经典的统计分析得到的结论更有效,尤其是针对隐性知识的量化上.结论将机器学习等计算机前沿技术引入考试测量领域,极大的拓宽了教育教学评价测量的模式.
Objective In order to improve the traditional statistics analysis which is used in the quondam system of Measurement of Test, increasing the depth and efficiency of Measurement of Test, improving educations and advancing the teaching quality in college. Methods Using to the traditional statistics analysis on the database of tests, a further analysis is applied, combining statistical analysis with Support Vector Machine （SVM）. Results The numeration result shows that the analysis result of combining statistical analysis with SVM is more effective than the conclusion obtained from the classical statistics, especially for the measurement to tacit knowledge. Conclusion Taking computer advanced technology, such as Machine Learning, into the domain of measurement of test, can extremely extend the mode of evaluation and measurement to education and teaching.
出处
《河北北方学院学报（自然科学版）》
2008年第5期67-70,80,共5页
Journal of Hebei North University:Natural Science Edition
关键词
教育测量
隐性知识
支持向量机
measurement of education
tacit knowledge
Support Vector Machine
