认知诊断中的Q矩阵及其作用

Q矩阵作为连接认知和测量的桥梁，在认知诊断中起重要作用。本文梳理了应用Q矩阵解决认知诊断相关问题的理论与方法。首先整理Q矩阵的相关概念、算法、性质及其在认知诊断中的作用；并根据Q矩阵可计算理论构念效度、可以构成格等，指出Q矩阵是特殊的关联矩阵；接着介绍Q矩阵理论研究方面的几个近期发展；并对Q矩阵未来的应用研究作出展望。期望本文能为测量工作者更灵活地利用Q矩阵提供参考和帮助。     

Self processing in the brain: A paradigmatic fMRI case study with a professional singer

Understanding the mechanisms involved in perception and conception of oneself is a fundamental psychological topic with high relevance for psychiatric and neurological issues, and it is one of the great challenges in neuroscientific research. The paradigmatic single-case study presented here aimed to investigate different components of self- and other-processes and to elucidate corresponding neurobiological underpinnings. An eminent professional opera singer with profound performance experience has undergone functional magnetic resonance imaging and was exposed to excerpts of Mozart arias, sung by herself or another singer. The results indicate a distinction between self- and other conditions in cortical midline structures, differentially involved in self-related and self-referential processing. This lends further support to the assumption of cortical midline structures being involved in the neural processing of self-specific stimuli and also confirms the power of single case studies as a research tool.     

Estimation of Group Priorities and Value of Information

In this paper, we present a Bayesian approach to model uncertainty about a group's priorities in a multicriteria evaluation problem and develop a methodology to quantify amount of information provided by a sample of priorities. In so doing, we discuss how the quantification of the information content can be used to decide to elicit additional priorities from the group. We illustrate the implementation of our approach and discuss additional insights that it provides using real‐life data from an academic department's priority analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

Typical hierarchical processing in autistic adults

ABSTRACT

Previous research suggests that autistic individuals exhibit atypical hierarchical processing, however, most of these studies focused solely on children. Thus, the main aim of the current study was to investigate the presence of atypical local or global processing in autistic adults using a traditional divided attention task with Navon’s hierarchical figures. Reaction time data of 27 autistic and 25 neurotypical (NT) adults was analysed using multilevel modelling and Bayesian analysis. The results revealed that autistic, like NT, adults experienced a global precedence effect. Moreover, both autistic and NT participants experienced global and local interference effects. In contrast to previous findings with children, the current study suggests that autistic adults exhibit a typical, albeit unexpected, processing of hierarchical figures.     

Analysis of meteorological conditions in Spain by means of clustering techniques

A comprehensive analysis of clustering techniques is presented in this paper through their application to data on meteorological conditions. Six partitional and hierarchical clustering techniques (k-means, k-medoids, SOM k-means, Agglomerative Hierarchical Clustering, and Clustering based on Gaussian Mixture Models) with different distance criteria, together with some clustering evaluation measures (Calinski–Harabasz, Davies–Bouldin, Gap and Silhouette criterion clustering evaluation object), present various analyses of the main climatic zones in Spain. Real-life data sets, recorded by AEMET (Spanish Meteorological Agency) at four of its weather stations, are analyzed in order to characterize the actual weather conditions at each location. The clustering techniques process the data on some of the main daily meteorological variables collected at these stations over six years between 2004 and 2010.     

Using movement and intentions to understand simple events

In order to understand ongoing activity, observers segment it into meaningful temporal parts. Segmentation can be based on bottom-up processing of distinctive sensory characteristics, such as movement features. Segmentation may also be affected by top-down effects of knowledge structures, including information about actors’ intentions. Three experiments investigated the role of movement features and intentions in perceptual event segmentation, using simple animations. In all conditions, movement features significantly predicted where participants segmented. This relationship was stronger when participants identified larger units than when they identified smaller units, and stronger when the animations were generated randomly than when they were generated by goal-directed human activity. This pattern suggests that bottom-up processing played an important role in segmentation of these stimuli, but that this was modulated by top-down influence of knowledge structures. To describe accurately how observers perceive ongoing activity, one must account for the effects of distinctive sensory characteristics, the effects of knowledge structures, and their interactions.     

Political opportunity structures and the activism of first- and second-generation Muslims in two Italian cities

ABSTRACT

The present contribution describes Muslims’ opportunities for activism and political participation, as shaped institutionally and discursively, in Milan and Turin. It analyses the interplay between the national level and the local level, and assesses the implications that contrasting local arrangements have for Muslims’ activism, claims-making and, to a certain extent, even self-identifications – especially with reference to young, second-generation Muslims. In Milan Muslims are confronted with a very closed system of political opportunities, while in Turin there appears to be a much more open system, which aims at co-opting second-generation organisations in particular. The consequence is that while in Milan Muslims – especially second-generation ones – are resigned to being merely the recipients of integration policies, in Turin they can conceive themselves more as partners of the city’s institutions, by resorting to a strategy of ‘active citizenship’.     

A diagnostic tree model for polytomous responses with multiple strategies

Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students’ problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students’ partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM.