基于行为事件的履历资料评估

行为事件的履历资料评估能有效克服传统履历数据构思效度弱、情景限制多等问题。本研究结合某通信企业招聘工作,选取250名应聘者数据,结合关键事件法,通过对履历事件的行为锚定来评估应聘者的胜任特征。研究在多重比较行为履历资料、履历表数据、认知能力等多个指标组合对录用结果预测的回归模型基础上,检验新增指标的预测效度。结果表明,行为事件的履历资料评估具有效标关联效度,与其他工具组合使用时具有增量效度。     

反馈延迟与掩蔽类型对知觉类别学习的影响

通过两个实验探讨反馈延迟与掩蔽类型对知觉类别学习的影响。实验1光栅掩蔽条件下,采用2（类别结构：基于规则vs.信息整合）×2（延迟反馈：500vs.3000ms）被试间实验设计,实验2采用同样的实验设计,保持延迟反馈时间不变,但改掩蔽类型为黑屏掩蔽。结果发现：（1）光栅掩蔽条件下,反馈延迟削弱信息整合类别结构的成绩,不影响基于规则类别学习,内隐外显类别结构之间存在分离效应。（2）黑屏掩蔽条件下,信息整合与基于规则类别结构的成绩均不受到延迟反馈的影响,分离效应消失。实验说明“无关因素”掩蔽影响知觉类别学习,知觉噪音与标准噪音在反馈延迟影响知觉类别学习中起到重要作用,COVIS模型理论关于延迟反馈时间影响知觉类别学习的解释具有局限性。     

不同认知结构被试的测验设计模式

正如不同的病症需要使用不同的医疗技术方法来诊断一样, 不同的认知结构也需要设计对应的测验模式来进行诊断, 从而保证测验具有高质量的诊断评估效果。但传统测验形式未考虑不同认知结构的针对性诊断测验需求, 导致“千人一卷”在测验效率上有所不足; 认知诊断计算机化自适应测验虽可针对不同认知结构的被试施测不同的项目, 然而支持自适应过程的题库却没有针对不同认知结构被试设计对应的项目, 导致题库使用效率较低。要解决上述问题的关键在于, 探索如何针对不同认知结构设计相对应的测验模式。本研究采用Monte Carlo模拟, 对六种属性层级关系下, 不同认知结构的测验设计模式进行探讨。实验结果表明(1)同一属性层级关系下, 不同认知结构的最佳测验设计模式不同; (2)依据不同认知结构的最佳测验设计模式构建的题库具有更高的使用效率。测验编制者可以根据实验结果针对不同认知结构优化对应的测验设计模式, 并用于指导题库建设。     

Personality in middle childhood: A hierarchical structure and longitudinal connections with personality in late adolescence

Research on the structure of personality in middle childhood, while advancing, is still in the early stages of development. In this study, we employed a group of 1563 twins to elucidate the hierarchical structure of personality in middle childhood and provide connections to established personality traits in adult populations. Our results provide evidence for a higher-order structure of personality in middle childhood that maps on to recent findings in adult populations supporting hierarchical relationships among 2-, 3-, 4-, and 5-factor models of personality. In addition, primary higher-order personality traits rated by parents at age 11 showed substantial predictive validity for analogous traits rated by self at age 17. We discuss our results within the context of developing a convergent hierarchical taxonomy of personality in middle childhood and the importance of multi-informant investigations.     

The origins of causal perception: evidence from postdictive processing in infancy

The currency of our visual experience consists not only of visual features such as color and motion, but also seemingly higher-level features such as causality--as when we see two billiard balls collide, with one causing the other to move. One of the most important and controversial questions about causal perception involves its origin: do we learn to see causality, or does this ability derive in part from innately specified aspects of our cognitive architecture? Such questions are difficult to answer, but can be indirectly addressed via experiments with infants. Here we explore causal perception in 7-month-old infants, using a different approach from previous work. Recent work in adult visual cognition has demonstrated a postdictive aspect to causal perception: in certain situations, we can perceive a collision between two objects in an ambiguous display even after the moment of potential 'impact' has already passed. This illustrates one way in which our conscious perception of the world is not an instantaneous moment-by-moment construction, but rather is formed by integrating information over short temporal windows. Here we demonstrate analogous postdictive processing in infants' causal perception. This result demonstrates that even infants' visual systems process information in temporally extended chunks. Moreover, this work provides a new way of demonstrating causal perception in infants that differs from previous strategies, and is immune to some previous types of critiques.     

Using relational structure to detect symmetry: a Voronoi tessellation based model of symmetry perception

Numerous models of symmetry perception have been proposed in recent years. Unfortunately, it is difficult to assess the relative utility of these models as little effort has been made to directly compare them. This paper outlines a new model of symmetry perception based upon the relational structure revealed by Voronoi tessellation. The model has been developed in response to evidence suggesting that the human visual system is generating a Voronoi-like representation at an early stage in processing. Bayesian model selection is employed to compare the performance of the Voronoi model to that of five previously published models across six empirical datasets. The results indicate that the Voronoi model provides a more likely account of the data than the five alternative models.     

Inhibition in Goal Systems: A Retrieval-Induced Forgetting Account

In social psychological models of goals, particular means or goals that receive more activation are pursued while their counterparts are “inhibited.” To account for inhibition, these theories emphasize structural distribution of resources and the consequences of goal or means choices. Absent are alternate accounts of inhibition based on memory processes that rely on retrieval or recall of items. We propose that the act of recalling means or goals from memory entails inhibition of competing alternatives. Two experiments using repeated retrieval paradigms present evidence that recalling one means associated with a particular goal inhibits competing means. Moreover, this inhibitory mechanism is sensitive to the structural relationship of goals and means. Implications for models of inhibition in goal pursuit are discussed.     

Categories and Dimensions

ABSTRACT— The distinction between categories and dimensions has important consequences for basic and applied science in many areas of psychological research. Decisions as to whether individuals should be assigned to groups or located along one or more continua often are based on personal preferences or discipline-specific measurement traditions, which can lead to the creation, use, or reification of spurious categories or dimensions. Methods for evaluating the latent structure of psychological constructs, using powerful and informative tests between competing models, are available. Rather than choosing on a priori grounds, investigators can perform structural research to evaluate the strength and consistency with which results tease apart categorical and dimensional models. Here, we review why researchers should make this distinction empirically, briefly discuss methods available for doing so, and describe the breadth of areas ripe for exploiting the largely untapped potential of structural research.     

A computational model of early argument structure acquisition

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning mechanisms that can grasp generalizations from examples of specific usages, and that exhibit patterns of behavior over the course of learning similar to those in children. Early learning of verb argument structure is an area of language acquisition that provides an interesting testbed for such approaches due to the complexity of verb usages. A range of linguistic factors interact in determining the felicitous use of a verb in various constructions —associations between syntactic forms and properties of meaning that form the basis for a number of linguistic and psycholinguistic theories of language. This article presents a computational model for the representation, acquisition, and use of verbs and constructions. The Bayesian framework is founded on a novel view of constructions as a probabilistic association between syntactic and semantic features. The computational experiments reported here demonstrate the feasibility of learning general constructions, and their exceptions, from individual usages of verbs. The behavior of the model over the timecourse of acquisition mimics, in relevant aspects, the stages of learning exhibited by children. Therefore, this proposal sheds light on the possible mechanisms at work in forming linguistic generalizations and maintaining knowledge of exceptions.     

Designing Urban Experiences. The Case of Zuidas,Amsterdam

Zuidas is a new city centre, which is emerging in the outskirts of Amsterdam. The ambitious project of developing a new international city centre has been carefully planned as the Netherlands has a strong and meticulous tradition for urban planning. The planning has however not only encompassed traditional urban planning aspects such as infrastructure, environmental factors and aesthetics, but has also dealt with the design of urban experiences. Through an introduction of the framework of the structure of experiences, this article examines how urban experiences can be understood and analysed, and deals with how urban experiences can be designed through careful consideration of how experiences are constituted. Taking the psychological structure of experiences into account when designing urbanity is not only interesting, but also highly relevant as Zuidas is competing with other international venues such as La Défense, the Docklands and Potsdamer Platz.