3V-JMLE法:计算机自适应测试中一种基于三值矩阵的联合参数估计方法
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摘要
文章对计算机自适应测试中常用的参数估计法——联合极大似然估计(Joint Maximum Likelihood Estimation,JMLE)法进行了改进,提出了一种基于三值矩阵的联合参数估计方法——3V-JMLE法。基于此,文章以作答反应数据库中被试作答信息为样本,分别采用JMLE法、3V-JMLE法进行参数估计,其对比结果表明:在理想作答矩阵下,3V-JMLE法和JMLE法具有同等的参数估计精度和计算效率;在非理想作答矩阵下,采用JMLE法进行参数估计存在一定的局限性,而采用3V-JMLE法具有很高的参数估计精度并大大提高了计算效率。3V-JMLE法的提出,对于联合参数估计方法的实际估计参数过程有重要指导意义。
In this paper, the parameter estimation method commonly used in computer adaptive testing, the joint maximum likelihood estimation(JMLE) method, was improved. Meanwhile, a joint parameter estimation method based on three-valued matrix, abbreviated as 3 V-JMLE method, was proposed. Based on this, the paper took the tested answer information in the answer response database as the sample, and used the JMLE and 3 V-JMLE methods to conduct the parameter estimation, respectively. The comparison results showed that JMLE method and 3 V-JMLE method had same level of parameter estimation accuracy and calculation efficiency under the ideal answer matrix. However, under the non-ideal answer matrix, the JMLE method had certain limitations in the parameter estimation, while the 3 V-JMLE method had high parameter estimation accuracy and greatly improved the calculation efficiency. The proposal of3 V-JMLE method had important guiding significance for the actual estimation parameter process of the joint parameter estimation method.
In this paper, the parameter estimation method commonly used in computer adaptive testing, the joint maximum likelihood estimation(JMLE) method, was improved. Meanwhile, a joint parameter estimation method based on three-valued matrix, abbreviated as 3 V-JMLE method, was proposed. Based on this, the paper took the tested answer information in the answer response database as the sample, and used the JMLE and 3 V-JMLE methods to conduct the parameter estimation, respectively. The comparison results showed that JMLE method and 3 V-JMLE method had same level of parameter estimation accuracy and calculation efficiency under the ideal answer matrix. However, under the non-ideal answer matrix, the JMLE method had certain limitations in the parameter estimation, while the 3 V-JMLE method had high parameter estimation accuracy and greatly improved the calculation efficiency. The proposal of3 V-JMLE method had important guiding significance for the actual estimation parameter process of the joint parameter estimation method.
引文
[1]张华华,程莹.计算机化自适应测验(CAT)的发展和前景展望[J].考试研究,2005,(1):12-24.
[2]Weiss D J. Improving measurement quality and efficiency with adaptive testing[J]. Applied Psychological Measurement, 1982,(4):473-492.
[3]Lord F M. An application of confidence intervals and of maximum likelihood to the estimation of an examinee’s ability[J]. Psychometrika, 1953,(1):57-76.
[4]游晓锋.CAT中原始题项目参数的估计[D].南昌:江西师范大学,2008:117-136.
[5]顾海根.人员测评[M].合肥:中国科学技术大学出版社,2005:236-240.
[6]罗芬,丁树良,胡小松,等.基于IRT若干参数估计方式的比较[J].江西师范大学学报(自然科学版),2003,(1):56-60.
[7]蔡艳.CAT中能力参数估计方法的改进:R-MLE估计法[J].心理学探新,2016,(1):92-96.
[8]刘丽平,王文杰,郭世宁.计算机自适应考试(CAT)系统题库的设计与实现[J].计算机系统应用,2006,(3):10-12、16.
[9]Van der Linden W J, Glas C A. Elements of adaptive testing[M]. New York:Springer, 2010:5-6.
[10]周宏,姚媛媛,顾小清.支持无缝翻转环境的语言学习框架建构与研究[J].现代教育技术,2017,(2):99-106.
[2]Weiss D J. Improving measurement quality and efficiency with adaptive testing[J]. Applied Psychological Measurement, 1982,(4):473-492.
[3]Lord F M. An application of confidence intervals and of maximum likelihood to the estimation of an examinee’s ability[J]. Psychometrika, 1953,(1):57-76.
[4]游晓锋.CAT中原始题项目参数的估计[D].南昌:江西师范大学,2008:117-136.
[5]顾海根.人员测评[M].合肥:中国科学技术大学出版社,2005:236-240.
[6]罗芬,丁树良,胡小松,等.基于IRT若干参数估计方式的比较[J].江西师范大学学报(自然科学版),2003,(1):56-60.
[7]蔡艳.CAT中能力参数估计方法的改进:R-MLE估计法[J].心理学探新,2016,(1):92-96.
[8]刘丽平,王文杰,郭世宁.计算机自适应考试(CAT)系统题库的设计与实现[J].计算机系统应用,2006,(3):10-12、16.
[9]Van der Linden W J, Glas C A. Elements of adaptive testing[M]. New York:Springer, 2010:5-6.
[10]周宏,姚媛媛,顾小清.支持无缝翻转环境的语言学习框架建构与研究[J].现代教育技术,2017,(2):99-106.