项目反应理论观察分数核等值的影响因素

探究带宽选择方法、样本量、题目数量、等值设计、数据模拟方式对项目反应理论观察分数核等值的影响。通过两种数据模拟方式,获得研究数据,并计算局部与全域评价指标。研究发现,在随机组设计中,带宽选择方法表现相似;考生样本量和题目数量影响甚微。在非等组设计中,惩罚法与Silverman经验准则表现优异;增加题目量可降低百分相对误差和随机误差;增加样本量导致百分相对误差变大,随机误差减小。数据模拟方式可影响等值评价。未来应重点关注等值系统评估。     

The multidimensionality of test anxiety: A test of different models

Abstract

Confirmatory factor analysis was employed to test the multidimensional structure of test anxiety. Starting with the traditional two-factor model, it was of interest whether additional dimensions could still be represented by a single higher-order factor of test anxiety or whether the additional dimensions represented correlates of test anxiety. The Revised Test Anxiety (RTA) scale and the German Test Anxiety Inventory (TAI-G) were combined collecting data from a binational sample of 218 American and 218 German university students. Considering the statistical and theoretical aspects of model fit, they indicated that a model consisting of three primary factors (worry, emotionality, and lack of confidence) fit the data best. While distraction and self-efficacy may be regarded as correlates of test anxiety, lack of confidence was substantiated as a component of test anxiety. Implications for the conceptualization of the content domain and hence area of test anxiety were discussed.     

Dissociation of sensory facilitation and decision bias in statistical learning

ABSTRACT

The detection of regularities in the sensory environment, known as statistical learning, is an important brain function that has been observed in many experimental contexts. In these experiments, statistical learning of patterned sensory stimulation leads to improvements in the speed and/or accuracy with which subsequent stimuli are recognized. That is, statistical learning facilitates the transformation of sensory stimuli into motor responses, but the mechanism by which this occurs is unclear. Statistical learning could improve the efficiency of sensory processing, or it could bias responses toward particular outcomes. The distinction is important, as these different hypotheses imply different functions and different neural substrates for statistical learning. Here we address this problem by studying statistical learning as a decision-making process, which allows us to leverage the extensive computational literature on this topic. Specifically we describe a method for applying the Diffusion Decision Model (DDM) to isolate different sensory and cognitive processes associated with decision-making. The results indicate that statistical learning improves performance on a visual learning task in two distinct ways: by altering the efficiency of sensory processing and by introducing biases in the decision-making process. By fitting the parameters of the DDM to data from individual subjects, we find that the prominence of these two factors differed substantially across the population, and that these differences were predictive of individual performance on the psychophysical task. Overall, these results indicate that different cognitive processes can be recruited by statistical learning, and that the DDM is a powerful framework for detecting these influences.     

高中英语阅读测验中题组模型的选择与应用

本研究通过高中英语阅读测验实测数据,对比分析双参数逻辑斯蒂克模型 (2PL-IRT)和加入不同数量题组的双参数逻辑斯蒂克模型 (2PL-TRT), 探究题组数量对参数估计及模型拟合的影响。结果表明：(1) 2PL-IRT模型对能力介于-1.50到0.50的被试,能力参数估计偏差较大;(2)将题组效应大于0.50的题组作为局部独立题目纳入模型,会导致部分题目区分度参数的低估和大部分题目难度参数的高估;(3)题组效应越大,将其当作局部独立题目纳入模型估计项目参数的偏差越大。     

个体解决三项系列问题的心理模型

该研究设计了2种实验条件,对360名6-19岁个体解决三项系列问题的能力发展进行了研究,旨在讨论个体解决三项系列问题的心理模型的发展问题,结果表明：(1)6-19岁个体对三项系列问题中有必然逻辑答案的题目的判断能力的发展速度比较平稳;(2)个体对三项系列问题中有必然逻辑答案的题目的判断能力先于对没有逻辑答案的题目,6-9岁个体对三项系列问题中没有必然逻辑答案的题目的判断能力的发展速度低于10岁以后的个体;(3)空间模型、语义模型、语义一空间混合模型和枢纽项比较模型是相互补充的,是在不同认知发展阶段依一定次序,按一定的阶段逐渐形成的,经历了5个不同的发展阶段,最终形成以枢纽项比较模型为核心、四种心理模型并存于个体的心理结构之中的复合模型。     

群体水平领域分数及其估计方法

对人才的需求已经引起各国政府和国际组织对教育的高度重视,纷纷在国家和地区层面进行大规模的教育评估。在大尺度教育评估中,如何向政府、管理者和公众报告学生表现是不可避免的重要问题。报告学生表现有多种方式,领域分数作为管理者和公众最容易理解和接受的分数报告工具之一,在近些年受到研究者和实践者的关注,因此也成为了大型教育评价项目的必然选择。文中将介绍群体领域分数的起源和定义,并重点介绍群体领域分数的估计方法和相关研究,最后对未来开展进一步研究进行展望。