An Automated Item Pool Assembly Framework for Maximizing Item Utilization for CAT

Computerized adaptive testing (CAT) has gained deserved popularity in the administration of educational and professional assessments, but continues to face test security challenges. To ensure sustained quality assurance and testing integrity, it is imperative to establish and maintain multiple stable item pools that are consistent in terms of psychometric characteristics and content specifications. This study introduces the Honeycomb Pool Assembly (HPA) framework, an innovative solution for the construction of multiple parallel item pools for CAT that maximizes item utilization in the item bank. The HPA framework comprises two stages—cell assembly and pool assembly—and uses a mixed integer programming modeling approach. An empirical study demonstrated HPA's effectiveness in creating a large number of parallel pools using a real-world high-stakes CAT assessment item bank. The HPA framework offers several advantages, including (a) simultaneous creation of multiple parallel pools, (b) simplification of item pool maintenance, and (c) flexibility in establishing statistical and operational constraints. Moreover, it can help testing organizations efficiently manage and monitor the health of their item banks. Thus, the HPA framework is expected to be a valuable tool for testing professionals and organizations to address test security challenges and maintain the integrity of high-stakes CAT assessments.     

数据挖掘在数据分析中的应用

本文针对运用数据挖掘方法构建规则库的过程进行阐述,对选取的算法进行介绍及确定其中的可变量,并着重解决方法运用过程中面临的若干问题,其中包括审计数据的收集、格式转换、规则集合并、规则匹配等。通过对挖掘结果的分析可以看出,将数据挖掘技术应用到数据分析中,大大提高了入侵检测系统的可靠性和智能化程度。     

基于IRT的自动组卷算法模型研究

基于项目反应理论(IRT),采用离差加权值最小和测验项目信息函数值最高两个目标规划相结合的办法,设计了一个新的自动组卷数学模型。该模型克服了经典测量理论(CTT)的种种局限,有效解决了计量指标——信息量与非计量指标——题型分布、知识点分布等约束条件计算量纲不同的问题,很好地体现了测试项目信息函数值最高的组卷目标。     

网络信息过滤的方法和技术研究

论述了网络信息过滤的原理,从用户的信息需求与表示、文本的表示技术等方面探讨了网络信息过滤的方法和技术以及存在的问题,提出Vague集之间的相似度量在网络信息过滤中的应用。     

一种新型的水下探测目标自动识别系统

利用布里渊散射提出了一种基于人工神经网络的水下探测目标识别系统,并在神经网络中引入动量项和采用可变步长。经过计算机仿真实验,结果表明：与传统的水下探测目标识别系统相比,该识别系统在识别时间和识别率两方面都得到了较大的改善．这些优点对实现水下探测目标的实时自动识别是极其有利的。     

高中学业水平考试研究(二):考试质量评价

学业水平考试试题和试卷的质量直接影响学业评价和诊断结果的有效性和可靠性。本文以上海市高中思想政治学科学业水平考试为例,从试题和题组功能偏差、试题得分与总分的相关系数、识别指数分析及分类一致性和准确性四个方面对考试的质量进行了定量评价,以介绍学业水平考试质量评价的方法。     

项目反应理论测验信度及其研究述评

项目反应理论下的测验信度能够评价潜在特质估计的可靠性与稳定性,由于具有宏观性的特点,项目反应理论信度的作用并不能被测验信息函数所取代,是IRT测验的一个重要指标。本文参考国内外文献,首先介绍国内外学者关于IRT信度作用的观点,并介绍和评价了多种IRT信度估计方法,然后简要介绍IRT信度的影响因素,最后展望了IRT信度领域后续研究尚可着力之处。     

Addressing the Lack of Measurement Invariance for the Measure of Acceptance of the Theory of Evolution

The Measure of Acceptance of the Theory of Evolution (MATE) was constructed to be a single-factor instrument that assesses an individual's overall acceptance of evolutionary theory. The MATE was validated and the scores resulting from the MATE were found to be reliable for the population of inservice high school biology teachers. However, many studies have utilized the MATE for different populations, such as university students enrolled in a biology or genetics course, high school students, and preservice teachers. This is problematic because the dimensionality and reliability of the MATE may not be consistent across populations. It is not uncommon in science education research to find examples where scales are applied to novel populations without proper assessment of the validity and reliability. In order to illustrate this issue, a case study is presented where the dimensionality of the MATE is evaluated for a population of non-science major preservice elementary teachers. With this objective in mind, factor analytic and item response models are fit to the observed data to provide evidence for or against a one-dimensional latent structure and to detect which items do not conform to the theoretical construct for this population. The results of this study call into question any findings and conclusions made using the MATE for a Hispanic population of preservice teachers and point out the error of assuming invariance across substantively different populations.     

数据挖掘中的关联规则方法

介绍了关联规则的基本概念,总结了关联规则的分类及各种挖掘算法,并对一些典型算法进行了介绍,最后展望了关联规则挖掘的下一步研究方向。     

粗糙集AHP融合模型在IT项目风险分析中的应用

IT项目是高投入、高风险产业,为了在IT项目开发中获得高收益,有必要对IT项目风险进行分析。但是传统分析方法比较主观,难以对IT项目风险进行客观的分析。文章先引入粗糙集理论,利用可分辨矩阵约简算法对IT项目风险表进行属性约简,剔除其中不必要的属性,然后综合利用粗糙集理论和AHP方法来确定IT项目风险的权重,并通过实例验证该方法的可行性和合理性。