不同文章难度条件下文化特征类型熟悉度对阅读理解的影响

该研究考察了非英语专业具有不同英语语言水平学习者在不同难度条件下两种文化特征熟悉度对阅读理解的影响。研究发现：（1）语言水平高,或对材料背景熟悉的学习者可通过调用熟悉的文化背景知识帮助阅读理解,其得分均高于低水平,或对材料不熟悉的学习者;（2）在熟悉的文化背景条件下,当材料难度与学习者语言水平基本一致时,语言水平低的学习者也可较好地运用熟悉的文化背景知识帮助阅读理解。实验结果表明：文化特征的内容熟悉度和英语语言水平（或文章难度）对阅读理解起着重要作用,语言水平越高,作用越大。     

解析心理冲突的新角度--评介凯根的结构-发展理论

本文介绍了自我发展研究领域中罗伯特凯根提出的结构-发展理论及其特点,简析它与其它自我发展阶段论的异同。探讨了该理论在抚育、学校教育和临床咨询等方面的实践意义。     

劳丹的研究传统理论对心理学研究的启示

劳丹的研究传统理论是在克服库恩“范式论”和拉卡托斯“研究纲领理论”不足的基础上建立起来的更为严密、更符合科学历史事实的理论体系,本文简要介绍了该理论并在此基础上提出了心理学研究从中得到的几点启示：心理学研究应从“以方法为中心”转向“以问题为中心”,采用概念分析等多元研究方法,以一种宽容、开放的态度来评价心理学的各种理论。     

表现性评价中评分者信度估计方法的比较研究--从相关法、百分比法到概化理论

随着素质教育的推进．表现性评价受到越来越多的重视。影响表现性评价结果信度的一个重要因素是评分者之间的不一致。文章使用模拟数据,在对比评分者一致性的相关法、一致性百分比法和概化系数等各种估计方法的基础上,提出概化理论在表现性评价中评分者信度问题上的应用是理论和实践发展的有益方向。     

幼儿说谎认知的年龄特征及其与心理理论水平的关系

研究探讨了3～4岁幼儿说谎认知的年龄特征,并在此基础上考察了说谎的概念理解水平与道德评价之问的关系,及说谎认知与心理理论水平的关系。结果表明：3岁和4岁幼儿在说谎和说真话概念的判断上年龄差异显著,在对说谎的道德评价上,年龄差异不显著;幼儿心理理论与说谎概念的相关显著,4岁组的心理理论与道德评价的相关显著。     

A formal framework for characterizing querying algorithms

Algorithmic procedures have been devised for constructing a knowledge space by querying experts. The queries submitted to the expert consist of assertions that are to be accepted or rejected. The present paper provides a characterization of the algorithms that may be used to draw inferences from previously collected answers. It is based on the notion of a closure on the set of all assertions, and its extension to a set containing for each assertion a positive and a negative instance, representing acceptance and rejection, respectively. The developed characterization emphasizes the significance of the well-known QUERY and PS-QUERY procedures. Potential applications of the presented results in contexts other than knowledge space theory are pointed out.     

Computer Implication and the Curry Paradox

There are theoretical limitations to what can be implemented by a computer program. In this paper we are concerned with a limitation on the strength of computer implemented deduction. We use a version of the Curry paradox to arrive at this limitation.     

Misreading Islamist Terrorism: The "War Against Terrorism" and Just-War Theory

Abstract: The Bush administration's military war on terrorism is a blunt, ineffective, and unjust response to the threat posed to innocent civilians by terrorism. Decentralized terrorist networks can only be effectively fought by international cooperation among police and intelligence agencies representing diverse nation‐states, including ones with predominantly Islamic populations. The Bush administration's allegations of a global Islamist terrorist threat to the national interests of the United States misread the decentralized and complex nature of Islamist politics. Undoubtedly there exists a “combat fundamentalist” element within Islamism. But the threat posed to U.S. citizens by Islamist terrorism neither necessitates nor justifies as a response massive military invasions of other nations. Not only does the Bush administration's war on alleged “terrorist states” violate the doctrine of just war, but in addition these wars arise from a new, unilateral, imperial foreign‐policy doctrine of “preventive wars.” Such a doctrine will isolate the United States from international institutions and long‐standing allies. The weakening of these institutions and alliances will only weaken the ability of the international community to deter terrorism.     

Higher-order latent trait models for cognitive diagnosis

Higher-order latent traits are proposed for specifying the joint distribution of binary attributes in models for cognitive diagnosis. This approach results in a parsimonious model for the joint distribution of a high-dimensional attribute vector that is natural in many situations when specific cognitive information is sought but a less informative item response model would be a reasonable alternative. This approach stems from viewing the attributes as the specific knowledge required for examination performance, and modeling these attributes as arising from a broadly-defined latent trait resembling theϑ of item response models. In this way a relatively simple model for the joint distribution of the attributes results, which is based on a plausible model for the relationship between general aptitude and specific knowledge. Markov chain Monte Carlo algorithms for parameter estimation are given for selected response distributions, and simulation results are presented to examine the performance of the algorithm as well as the sensitivity of classification to model misspecification. An analysis of fraction subtraction data is provided as an example. This research was funded by National Institute of Health grant R01 CA81068. We would like to thank William Stout and Sarah Hartz for many useful discussions, three anonymous reviewers for helpful comments and suggestions, and Kikumi Tatsuoka and Curtis Tatsuoka for generously sharing data.