"条""块"结合,构建班级德育评价模式

德育评价是德育工作的难点,通过对学生道德发展水平"块"、教师德育工作水平"块"及班级德育内容要素"条"三个项目的分别细化和综合汇总,得出对一个班级德育工作的比较客观规范的评价,是对德育评价模式进行的有益探索.     

数据挖掘技术在高校教学质量评价中的应用

针对高校教学质量评价,利用数据挖掘技术,运用多种数据挖掘方法对教学相关数据进行分析,以期达到改进教学方法,提高教学质量的目的。     

Scientific reasoning in elementary school children: Assessment and relations with cognitive abilities

The primary goal of this study was the broad assessment and modeling of scientific reasoning in elementary school age. One hundred fifty-five fourth graders were tested on 20 recently developed paper-and-pencil items tapping four different components of scientific reasoning (understanding the nature of science, understanding theories, designing experiments, and interpreting data). As confirmed by Rasch analyses, the scientific reasoning items formed a reliable scale. Model comparisons differentiated scientific reasoning as a separate construct from measures of intelligence and reading skills and revealed discriminant validity. Furthermore, we explored the relationship between scientific reasoning and the postulated prerequisites inhibitory control, spatial abilities and problem-solving skills. As shown by correlation and regression analyses, beside general cognitive abilities (intelligence, reading skills) problem-solving skills and spatial abilities predicted performance in scientific reasoning items and thus contributed to explaining individual differences in elementary school children's scientific reasoning competencies.     

基于事务压缩的Apriori算法的改进

在数据挖掘算法中，Apriori算法是关联规则的经典算法。文章在分析经典Apriori算法的基础上，提出了改进型的Apriori算法。改进后的算法对事务数据库进行两次压缩，减少事务数据库的平均长度，提高了数据挖掘的效率，具有一定的实用性。     

New evidence on the validity of the Arnett Caregiver Interaction Scale: Results from the Early Childhood Longitudinal Study-Birth Cohort

The Arnett Caregiver Interaction Scale (CIS) has been widely used in research studies to measure the quality of caregiver–child interactions. The scale was modeled on a well-established theory of parenting, but there are few psychometric studies of its validity. We applied factor analyses and item response theory methods to assess the psychometric properties of the Arnett CIS in a national sample of toddlers in home-based care and preschoolers in center-based care from the Early Childhood Longitudinal Study-Birth Cohort. We found that a bifactor structure (one common factor and a second set of specific factors) best fits the data. In the Arnett CIS, the bifactor model distinguishes a common substantive dimension from two methodological dimensions (for positively and negatively oriented items). Despite the good fit of this model, the items are skewed (most teachers/caregivers display positive interactions with children) and, as a result, the Arnett CIS is not well suited to distinguish between caregivers who are “highly” versus “moderately” positive in their interactions with children, according to the items on the scale. Regression-adjusted associations between the Arnett CIS and child outcomes are small, especially for preschoolers in centers. We encourage future scale development work on measures of child care quality by early childhood scholars.     

三参数等级反应模型及其信息函数的应用

项目反应理论（Item Response Theory,IRT）是现代教育心理测量领域中最有影响的一种测量理论,它的一个明确目标是扩展模型的种类以至于能够处理实际测试中任何形式的反应数据。在已有的各种模型研究中,对于多级评分项目,只考虑到项目区分度和难度。但在实际测验中,此类项目还可能存在猜测度。本研究基于Samejima等级反应模型,将项目猜测度融合到多级评分模型中,提出了三参数等级反应模型（Three-parameter Graded Response Model,3PL-GRM）。由于忽略多级反应项目的猜测度会使得该项目的信息量虚假升高,本研究还进一步将3PL—GRM的信息函数应用到试卷质量分析中。     

数据挖掘中一种改进的Apriori算法

关联规则挖掘是数据挖掘领域中的一个非常重要的研究内容,其主要目标就是发现数据库中一组对象之间某种关联。频繁项集挖掘是关联规则挖掘的关键步骤,它在很大程度上决定了关联规则挖掘的效率。介绍了Apriori算法及其算法改进。该改进算法对剪枝步进行了优化,提高了连接效率,并且不断减小数据库的规模,去掉无效事务,减少了每次扫描数据库所花费的时间,提高了算法效率。经过试验论证,性能比原有算法提高,具有一定的实用性。     

数据挖掘中关联规则算法的研究

Apriori算法是关联规则挖掘中的经典算法。通过对Apriori算法的基本思想和性能的研究分析,提出了一种基于垂直事务列表的树形结构的挖掘算法,减少了候选频繁项集的数量,提高了挖掘算法的效率。实验结果表明新算法具有良好的性能。     

基于项目反应理论的自适应考试系统

计算机自适应考试是建构在项目反应理论基础上的一种考试方式,它能根据考生答题的情况不断计算受试者的能力值及信息量,并实时地根据这些参数调整出题策略,使用计算机自适应考试可以更真实地反映受试者的水平和特点。     

英美图书馆立法进程比较和启示

制定《公共图书馆法》,是当前我国图书馆界的焦点话题,需从国外特别是发达国家汲取经验。本文以英美为例,比较了二者图书馆立法进程。对比分析两国图书馆立法进程,对我们有十分重要的启示。