学生评价教师绩效的结构验证性因素分析

文章采用开放式调查、关键事件访谈、理论分析等方法建构了教师绩效的结构,并通过验证性因索分析验证了学生评价教师绩效的结构包含6个一阶因子,即职业道德、职务奉献、助人合作、教学效能、教学价值与师生互动,这6个因子组成了2个二阶因子,前3个因子属于关系绩效,后3个因子属于任务绩效。     

商讨理论视野中的伦理、民主、人权和民族国家

本文根据哈贝马斯的访华演讲和相关著述,对商讨理论视野中的伦理、民主、人权和民族国家概念进行了考察,并在此基础上提出了某些基本的判断和论点。     

中小学生体育锻炼感觉和体育运动动机与心理健康关系的研究

采用心理测量法对中小学生目标人群进行体育锻炼感觉量表(EFI)、体育运动动机量表(SMS)和心理健康诊断测验(MHT)等量表的测试,并以路径分析的方法来确定量表各维度之间的相互关系,探讨这些维度对学生总体心理健康水平的影响途径和力度。结果表明：(1)学生参加体育活动的积极性、体育活动后的疲劳程度和参与体育活动的外部动机直接影响学生的心理健康。(2)内部动机是导致心理健康产生变化的根本因素,通过体育活动提高学生心理健康水平的主要途径是强化学生参与体育活动的内部动机。     

Non‐linear structural equation models with correlated continuous and discrete data

Structural equation models (SEMs) have been widely applied to examine interrelationships among latent and observed variables in social and psychological research. Motivated by the fact that correlated discrete variables are frequently encountered in practical applications, a non‐linear SEM that accommodates covariates, and mixed continuous, ordered, and unordered categorical variables is proposed. Maximum likelihood methods for estimation and model comparison are discussed. One real‐life data set about cardiovascular disease is used to illustrate the methodologies.     

正常和弱视者立体和形状视觉感知时间的差异

在速示器,以随机点立体图对为刺激,测量了正常和弱视者的立体视和形状视感知时间。实验表明:正常被试需要大约100ms感知深度,110ms或更长时间感知形状。这二种感知时间与刺激视差的种类和大小无关。弱视者需要比正常人较长的时间达到立体和形状的视感知。这二种感知时间的差别,弱视者也大于正常人。视锐度和立体视范围均恢复到正常的弱视者,以上二种感知时间,可以达到正常人范围,也可能显著地大于正常人。     

机器理解古汉语的实验和若干问题

本文介绍了机器理解古汉语的一个实验系统(ACLUS)。该系统由一个知识库和三个子程序组成。知识库包含有一部机器词典和若干集用来加工句子的规则。三个子程序是:句法分析子程序、翻译子程序和问答子程序,它们分别执行三种不同的功能。本文还讨论了有关机器理解古汉语的若干重要问题。     

痛成分的心理学研究

近年来.疼痛原理的研究有了迅速的发展,最近提出了针刺对痛的不同成分的影响问题。关于痛的问题,至今尚没有它的科学定义。十九世纪以前,有人把痛看作是紧密地和不愉快的情绪相联系的;自本世纪以来,痛是感觉的观点占了优势。人们都承认痛不同于视、听等感觉,因为它还带有明显的情绪色彩。心理学和生理学教科书中,一方面说痛     

痛成分的心理学研究(Ⅱ)——试论穴位电针的镇痛效应

在针麻原理的研究中,有人探讨了入手术室时的情绪状态和某些心理、生理机能的联系及其和针麻效果的关系。那么针刺对情绪有何影响?在前一个研究中,我们提出了痛反应量表,考察多种痛刺激下的情绪状态和痛感觉。然后再在受试者身上进行同神经     

Aiming at Happiness: How Motivation Affects Attention to and Memory for Emotional Images

Socioemotional Selectivity Theory (Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). American Psychologist, 54, 155–181) posits that older adults, and anyone else who perceives their time as limited, show a motivational shift toward emotion regulation which causes them to exhibit a positivity bias and negativity avoidance in attention and memory. We tested whether such a motivational shift can indeed cause changes in emotional processing by manipulating motivation in a sample of young adults. After the manipulation, participants looked at real-world images while their eye movements were tracked. It was found that participants motivated to regulate emotion attended less to negative than positive images and showed less looking time to all stimulus types compared to the other two conditions. No evidence was found linking the motivational manipulation to emotional memory.

Two efficient selection methods for high-dimensional CD-CAT utilizing max-marginals factor from MAP query and ensemble learning approach

Computerized adaptive testing for cognitive diagnosis (CD-CAT) needs to be efficient and responsive in real time to meet practical applications' requirements. For high-dimensional data, the number of categories to be recognized in a test grows exponentially as the number of attributes increases, which can easily cause system reaction time to be too long such that it adversely affects the examinees and thus seriously impacts the measurement efficiency. More importantly, the long-time CPU operations and memory usage of item selection in CD-CAT due to intensive computation are impractical and cannot wholly meet practice needs. This paper proposed two new efficient selection strategies (HIA and CEL) for high-dimensional CD-CAT to address this issue by incorporating the max-marginals from the maximum a posteriori query and integrating the ensemble learning approach into the previous efficient selection methods, respectively. The performance of the proposed selection method was compared with the conventional selection method using simulated and real item pools. The results showed that the proposed methods could significantly improve the measurement efficiency with about 1/2–1/200 of the conventional methods' computation time while retaining similar measurement accuracy. With increasing number of attributes and size of the item pool, the computation time advantage of the proposed methods becomes more significant.