研究生入学考试写作评分的概化理论研究与多面Rasch分析

为了评价和改进硕士研究生入学考试一般能力测试的写作评分,研究者采用概化理论和多面Rasch分析对113位考生的写作样本的评分误差来源、评分信度等进行了探讨.概化理论研究显示,评分者和题目对评分准确性影响不大,以两道写作题的考试设计而言,评分者为2人即可保证评分信度在0.75以上.多面Rasch分析显示,评分者宽严度的估计值及其误差均在可接受的范围内,评分者之间在宽严度上不存在显著差异,且评分者自身在评分时总体上比较稳定.但个别评分者在特定考生特定题目上表现出特殊偏向.概化理论和多面Rasch分析丰富了写作评分研究的量化指标,证实了硕士研究生入学考试一般能力测试的写作评分具有较高的信度.     

CAT选题策略分类概述

选题是计算机化自适应测验（CAT）测试过程的关键环节,选题策略的目标是要达到较高的测量精度,同时也实现试题曝光率控制及其他测验目标的实现.本文根据选题策略的基本原理和衍生发展,将众多CAT选题策略分为五大选题策略系列：Fisher函数系列、K-LI函数系列、α分层系列、贝叶斯系列、b匹配系列;并根据测验目标（测验精度、试题曝光率控制、内容平衡、多条件约束）对这些选题策略进行了细分,并对CAT选题策略的选择思路进行归纳.     

Taking religion to heart: the relationship between the Five Factor Model and the New Indices of Religious Orientation among religious students

The relationship between religious orientation and personality has been investigated using several different measures and diverse samples. As part of a larger study, 114 undergraduate students were given the Duke University Religion Index (DUREL) to include only those participants who were considered religious. The final sample of 80 participants were given the NEO Personality Inventory-Revised (NEO PI-R) and the New Indices of Religious Orientation (NIRO). Based on the results of the bivariate correlations, higher levels of intrinsic religious orientation were associated with greater Agreeableness and Conscientiousness. Multivariate analyses further revealed that Agreeableness was the most important personality variable when predicting intrinsic and quest religious orientations, with higher levels of Agreeableness predicting greater intrinsic and lower quest orientations. While lower levels of Neuroticism predicted greater intrinsic orientation, higher levels of Neuroticism predicted greater quest orientations. Higher Conscientiousness predicted greater intrinsic and lower quest orientations. Implications of these findings are discussed.     

Bidirectional feature selection with global and local structure preservation for small size samples

Collecting samples is a challenging task for face recognition, especially for some real-world applications such as law enhancement and ID card identification, where there is usually single sample per person (SSPS) used to train a face recognition system. To extract discriminative features from the small size samples, in this paper we propose virtual samples via bidirectional feature selection with global and local structure preservation (VS-BFS-GL) to augment the number of training samples. In VS-BFS-GL, bidirectional feature selection is developed, which introduces L_2,1 norm to explore the face variations from both horizontal and vertical directions. Further, to include more variations in the virtual images, the global structure information and sample-specified local structure information of the SSPP training set are considered. By integrating bidirectional feature selection, global and local structure, the limited training samples are fully utilized and more knowledge are mined. To further improve the effectiveness of VS-BFS-GL, an auxiliary database containing different face variations can be used to explore the local structure information. We extensively evaluated the proposed approach on AR and FERET database. The promising recognition results demonstrate that VS-BFS-GL is robust to expression, pose and partial occlusion variations in the faces.     

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。     

探索语言水平测验的认知诊断改造和深度分析： 以广州市英语学业考试为例

本研究探索在通用认知诊断模型和相关检验方法的基础上对现有语言水平测验进行诊断改造和分析,分三步进行探索：1）探索对语言水平测试不同的属性和Q矩阵构建途径;2）探索对语言水平测试基于通用模型的建模和效度验证;3）探索对语言水平测试建模后续的深入分析。研究发现：属性分布和总分分布划分的学生水平一致性较高;学生对属性掌握存在性别差异且属性间的难易层级不同;属性模式分布进一步验证了语言属性间关联程度较高以及通用认知诊断模型和相关检验方法对语言测验的适用性。三步式的建模分析可作为对语言水平测验进行认知诊断改造的参考。     

Women’s hair as a cue to desired relationship and parenting characteristics

We investigated how women’s hair color (blond, brown, black) and length (short, medium, long) influences males’ judgments about the women’s age, health, physical attractiveness, relationship potential, and parenting capability. Results, which are generally consistent with evolutionary psychology approaches, indicate that hair color and, to a lesser extent, length can affect perceptions of personal characteristics. More specifically, we found that lighter hair (blond and brown) compared to darker hair (black) is generally associated with perceptions of youth, health and attractiveness, and generally leads to more positive perceptions of relationship and parenting potential. Furthermore, the relationships between variables suggest that characteristics directly related to reproductive potential may be inferred from more obvious indirect characteristics. These results suggest that males are able to make complex judgments about women concerning their desirable relationship and parenting potential based on discernable characteristics such as hair color and length.