假言推理的否定词效应

介绍假言推理中的4种否定词效应,以及相关的理论模型。被试在进行假言推理时,对前提或结论所表示的事件加进了否定词, 产生了一系列的心理效应。研究发现,范畴前提含有否定词,被试更难做出正确的推论;如果结论中含有否定词,被试却更容易做出正确的推论。为此,心理模型理论,规则理论,概率模型理论以及我国的学者对该问题都作了研究和阐述。     

问题解决中策略的变化：一项微观发生研究

以30名小学三年级儿童为被试,以一种特殊的方程问题为材料,采用微观发生法,先后进行了5次测查,收集了解题后的口语报告资料,从策略变化的路线、速率、广度、来源以及变化模式的多样性等方面详细探讨了问题解决策略的变化过程。结果发现,在面临新的问题时,被试缺乏相应知识和专门的解题策略,这时以使用多种常规策略以及错误策略为主;此后,当被试建构起对问题的正确表征时,就以使用正确策略为主,甚至发现了非常有技巧性和领域专门性的快捷策略,这时策略的数量明显减少;在面临难度较大的迁移题目时,快捷策略的使用率又降低,而更多借助于常规策略。可见,策略的获得是一个由错误到正确、由多种尝试到选择其一、由一般到专门的演化过程,这主要是一个学生自主建构的过程,当然也受到正式和非正式教育提供的知识的影响。值得说明的是,快捷策略的获得受到问题呈现模式的影响。总是呈现相同题目的单一模式有助于快捷策略的发现,而在混合训练中,插入不同性质的题目会干扰快捷策略的发现;但是,当面临迁移问题时,单一训练相比于混合训练的优势会消失。此外,正确使用常规策略是发现快捷策略的前提。     

Information matrix estimation procedures for cognitive diagnostic models

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance.     

听觉预测编码：对声音重复和变化的神经反应

预测编码被认为是脑与复杂环境交互的重要机制之一, 有效感知外界环境并对未来事件做出预测, 对个体生存有着至关重要的意义。人类大脑会基于感觉输入以迭代的方式持续优化表征外部环境的内部模型, 并不断预测接下来的感觉输入。以听觉模态为例, 人类及动物对声音重复和听觉变化的神经反应(如失匹配负波和刺激特异性适应)是大脑预测编码的重要体现, 表现为重复抑制和预测误差。结合人类和动物模型在此理论框架下开展跨物种研究将有助于加深我们对听觉加工, 甚至是大脑工作机制的认识。     

Perfectionism mediated the relationship between brain structure variation and negative emotion in a nonclinical sample

In maladaptive respects, perfectionism reflects an individual’s concern over making mistakes and doubting the quality of his or her own actions excessively, which would affect one’s emotion. However, little is known about the neural mechanisms associated with the perfectionism and negative affect. In this study, voxel-based morphometry was performed to identify the brain regions underlying individual differences in perfectionism, which was measured by the Chinese Frost Multidimensional Perfectionism Scale (CFMPS), in a large sample of nonclinical young adults. Our results showed that the two subdimensions of the perfectionism, concern over mistakes (CM) and doubts about actions (DA), were both positively correlated with the self-reported anxiety and depression as well as the gray matter volume (GMV) in the anterior cingulate cortex (ACC), a pivotal brain region in cognitive control, affective state, and regulation. Moreover, CM, DA, and organization scores were respectively correlated with distributed brain regions involved in multiple cognitive and emotion processes. Our results furthermore revealed that the score of DA acted a mediational mechanism underlying the relationship between the GMV of ACC and self-rating negative affect (anxiety and depression). Taken together, these results might suggest the neuroanatomical basis of perfectionism and the association among the perfectionism, negative emotion, and brain architecture. This study emphasized that perfectionism could play a crucial role in the arousal of negative affect.     

Trait compassion is associated with the neural substrate of empathy

Individual differences in the personality trait Agreeableness underlie humans’ ability to interpret social cues and coordinate effectively with others. However, previous investigations of the neural basis of Agreeableness have yielded largely inconsistent results. Recent evidence has demonstrated that Agreeableness can be divided into two, correlated subdimensions. Compassion reflects tendencies toward empathy, sympathy, and concern for others, while Politeness reflects tendencies toward compliance and refraining from aggression and exploitation. The present study seeks to clarify the neural substrates of Agreeableness by examining whether structural differences in the brain show distinct associations with Compassion and Politeness. Results of a meta-analysis of fMRI studies examining empathy were used to generate hypotheses about the brain regions and networks that underlie trait Compassion. Results of a large-scale structural neuroimaging investigation (N = 275) were largely consistent with the meta-analysis: Compassion was positively correlated with gray matter volume in the bilateral anterior cingulate cortex (ACC) and anterior insula (AI). Further, these differences appear to be associated with Compassion specifically, as opposed to Politeness, suggesting that these two traits have at least partially distinct neuroanatomical substrates.     

Developing new online calibration methods for multidimensional computerized adaptive testing

Multidimensional computerized adaptive testing (MCAT) has received increasing attention over the past few years in educational measurement. Like all other formats of CAT, item replenishment is an essential part of MCAT for its item bank maintenance and management, which governs retiring overexposed or obsolete items over time and replacing them with new ones. Moreover, calibration precision of the new items will directly affect the estimation accuracy of examinees’ ability vectors. In unidimensional CAT (UCAT) and cognitive diagnostic CAT, online calibration techniques have been developed to effectively calibrate new items. However, there has been very little discussion of online calibration in MCAT in the literature. Thus, this paper proposes new online calibration methods for MCAT based upon some popular methods used in UCAT. Three representative methods, Method A, the ‘one EM cycle’ method and the ‘multiple EM cycles’ method, are generalized to MCAT. Three simulation studies were conducted to compare the three new methods by manipulating three factors (test length, item bank design, and level of correlation between coordinate dimensions). The results showed that all the new methods were able to recover the item parameters accurately, and the adaptive online calibration designs showed some improvements compared to the random design under most conditions.     

流动儿童消极学业情绪对学习自我效能感的影响:情绪调节策略的调节作用

以397名流动儿童为被试,采用问卷法考察流动儿童消极学业情绪对学习自我效能感的影响以及情绪调节策略在其中的调节作用。结果表明：（1）流动儿童学业情绪对控制感的负向预测作用高于对基本能力感的预测作用,其中有恼火、羞愧、无助对基本能力感预测作用显著;认知重评对基本能力感预测作用显著,并且认知重评情绪调节策略对恼火、沮丧与基本能力感的关系有调节作用,而表达抑制对无助与基本能力感的关系有调节作用。（2）流动儿童学业情绪中除恼火外,焦虑、羞愧、厌倦、无助、沮丧和心烦对控制感的预测作用均显著。认知重评和表达抑制均对控制感的预测作用显著,并且认知重评与羞愧、厌倦、沮丧的调节作用显著,表达抑制与沮丧的调节作用显著。     

HO-GDINA模型的EM算法参数估计

Generalized DINA Model(G-DINA)为认知诊断模型提供了一个一般性的理论框架,而高阶诊断模型不仅能描述被试的总体水平,还能描述被试对属性的掌握情况(微观的认知状态)以及被试掌握属性与能力的关系,提供更丰富的信息。如果能把这两者结合起来,可能对实际诊断工作的操作有较大帮助。文章首先对考虑高阶结构的整合性模型——HO-GDINA模型的形式进行讨论,探讨其参数估计EM算法的实现,并用模拟过程对模型的估计精度进行研究,结果验证了HO-GDINA的EM算法的正确性,并且说明该算法对该模型有较高估计精确度。然后用饱和模型在约束条件下的特殊形式HO-DINA模型对"分数减法"这一经典数据进行EM算法参数估计和具体分析,展示了HO-GDINA在实际情况中的具体使用,并与de la Torre之前用MCMC估计算法得到的研究结果做比较,基本一致,进一步表明HO-GDINA模型的参数估计EM算法在实际情境中的特殊形式下仍然适用。