摘要
利用主成分分析方法厘清试题难度影响因素之间的关系,进而从问题表征、问题解决和结果输出等3个维度上建立了影响高中学业水平考试试题难度的主要因素。通过编写高中学业水平考试测试题进行实证研究,建立影响因素常见呈现类型的难易赋值规则。选用机器学习的线性回归方法建构试题难度分析模型,并使用高考化学江苏卷部分试题的实测难度数据进行校验,模型难度预测值和高考难度实测值具有较好的拟合度,表明模型具有较好的应用价值和推广意义。
This paper clarifies the relationship among the factors influencing item difficulty through the main-factor analysis method.On this basis,the main factors influencing item diffi-culty of senior high school achievement test are found from the three dimensions of problem rep-resentation,problem solving and result output.Next,through the writing and testing of items of alternate forms,the difficulty sequence of factors of different types and corresponding grading rules are established.After assigning values to the 7 factors of all the items of alternate forms,the linear regression method of machine learning is used to construct the model.In addition,the model is tested with data generated from part of the constructed items in college entrance exami-nation chemistry Jiangsu paper.The predicted value of the model and the measured value have a good degree of fit,indicating the application value and promotion significance of the model.
作者
刘芳
王伟群
吴星
LIU Fang;WANG Wei-Qun;WU Xing(Jiangsu Province Education Examination Authority,Nanjing 210024,China;College of Chemistry,Chemical Engineering and Materials Science,Soochow University,Suzhou 215123,China;College of Chemistry and Chemical Engineering,Yangzhou University,Yangzhou 225002,China)
出处
《化学教育（中英文）》
CAS
北大核心
2022年第21期43-47,共5页
Chinese Journal of Chemical Education
基金
国家教育考试科研规划2021年度课题“新高考制度下选择性考试命题质量保障机制研究”(GJK2021042)。
关键词
试题难度
影响因素
主成分分析
机器学习
线性回归
item difficulty
influencing factors
main factor analysis
machine learning
linear regression
