多级评分模型下的题库结构对CAT的影响分析

在多级评分模型下,项目的难度参数或步骤参数有多个,在对多级评分模型进行选题时,通常对项目的多个难度参数用一个综合的指标来概括.当对每个项目的难度参数进行有效的综合后,综合后的难度参数分布发生了改变,这时如果增加适量的平均难度较难或较易的项目进入题库,测验的精度和项目的曝光率都有一定的改善.     

大学生的基本兴趣及其与专业承诺的关系

该研究调查了1304名来自18个不同专业领域的大学生的基本兴趣和专业承诺,并用回归法分析了特定基本兴趣与专业承诺之间的关系.结果发现：（1）大学生的31种基本兴趣在二维空间中呈现近似圆形的排列,且基本兴趣结构上的性别差异不明显;（2）在14个专业领域内大学生的特定基本兴趣能显著预测其专业承诺,所解释的变异量平均为20％,接近中等水平的效果大小;（3）在不同专业领域内基本兴趣对专业承诺的影响效果大小有所不同.     

The driver behaviour questionnaire in South-East Europe countries: Bulgaria,Romania and Serbia

Using data from three samples and more than 1000 participants, this study have examined the psychometric properties of the Driver Behaviour Questionnaire (DBQ) in three countries from South-East Europe. Differences in driving behaviour between countries were also investigated. Exploratory factor analysis results supported the distinction between errors and violations in all three countries. Furthermore, the positive associations of both errors and violations with self-reported traffic accidents were also consistent in all three samples. In terms of differences in driving behaviour, Romanian drivers scored higher on many error and violation items in comparison to the other two countries. Also, speeding violations were the most common violations in all three countries. Overall, our results provide further support for using the DBQ to measure aberrant (i.e. errors and violations) driver behaviour.     

Bidirectional feature selection with global and local structure preservation for small size samples

Collecting samples is a challenging task for face recognition, especially for some real-world applications such as law enhancement and ID card identification, where there is usually single sample per person (SSPS) used to train a face recognition system. To extract discriminative features from the small size samples, in this paper we propose virtual samples via bidirectional feature selection with global and local structure preservation (VS-BFS-GL) to augment the number of training samples. In VS-BFS-GL, bidirectional feature selection is developed, which introduces L_2,1 norm to explore the face variations from both horizontal and vertical directions. Further, to include more variations in the virtual images, the global structure information and sample-specified local structure information of the SSPP training set are considered. By integrating bidirectional feature selection, global and local structure, the limited training samples are fully utilized and more knowledge are mined. To further improve the effectiveness of VS-BFS-GL, an auxiliary database containing different face variations can be used to explore the local structure information. We extensively evaluated the proposed approach on AR and FERET database. The promising recognition results demonstrate that VS-BFS-GL is robust to expression, pose and partial occlusion variations in the faces.     

School Perceptions of Children Raised by Grandparents

Increasing numbers of children raised by grandparents are students in schools. Their substitute family structure and precursors to the emergence of this family structure have implications for the children's school performance. Research suggests teachers view these children as at risk for difficult school functioning. The aforementioned judgment is problematic because teacher expectations, attributions, and biases are associated with stereotype threat that impacts student performance adversely. The author compares children raised by grandparents with children raised by parents and foster parents. The author examines the children's perceptions of their teachers' views of their school performance. He also examines the children's general feelings about school. Participants in the study were 6,550 students in Grades 6–8 from the nationally representative Health Behaviour in School-aged Children survey. Nonparametric statistical analyses reveal children raised by grandparents believe teachers' view their school performance negatively when compared with children living with both parents. Strategies are described to improve the children's performance in school and to foster favorable teacher perceptions.     

Kindergarteners' Narrative Competence Across Tasks and Time

The authors investigated children's narrative competence by analyzing the development of the reciprocal relationship between storytelling and story retelling performances over a school year through a cross-lagged panel design. The participants in this study were 170 Italian kindergarten pupils (M age = 4.98 ± 0.31 years). Children were asked to produce oral narratives in two different tasks: a storytelling and a story retelling task. Narrative competence was assessed in terms of structure and coherence. The cross-lagged panel analyses showed that both storytelling and story retelling tasks are stable constructs, but they differ in the emphasis on coherence. Data confirmed the pivotal role played by storytelling as a task, and structure as a component in fostering the development of children's narrative competence. Overall, results from this study suggest that storytelling and story retelling are tasks that involve interrelated but not overlapping processes, and trigger different aspects of narrative competence.     

THE FATHER,THE FATHER FUNCTION,THE FATHER PRINCIPLE: SOME CONTEMPORARY PSYCHOANALYTIC DEVELOPMENTS

The author discusses Freud's thinking on the role of the father, as well as that of later French theoreticians. To illustrate his remarks, he draws on the poetry of Carlos Drummond de Andrade (1912–1987), a Brazilian poet whose work often dealt with themes of the father, the family, and his own paternal relationship. The author also discusses the psychic formation of the father principle and how this may be evident in the clinical analytic setting, even when the analyst's approach privileges field theory, intersubjectivity, or other concepts emphasizing the relationship between analyst and patient.     

Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure

This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple‐group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy‐to‐use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large.     

A comparative assessment of the factor structures and psychometric properties of the GHQ-12 and the GHQ-20 based on data from a Finnish population-based sample

The General Health Questionnaire (GHQ) is a self-report questionnaire designed to identify psychological distress. Psychometric properties of two versions of GHQ-12 and GHQ-20 were assessed in a large population-based sample of Finnish twins, ages 22 to 27 (n= 4580). Participants were randomized into two subgroups, namely Twin1 (n= 2294) and Twin2 (n= 2286). The GHQ-12 data were assessed using Confirmatory Factor Analysis (CFA). The factor structure of the GHQ-20 was first assessed with Exploratory Factor Analysis (EFA) in the Twin1 dataset, and the results obtained were then subjected to CFA in Twin1 and Twin2 datasets. The CFA of the GHQ-12 indicated that the best fit and the simplest solution were provided by the three-factor solution in both subpopulations. Analyses of the GHQ-20 suggested that the four-factor structure was superior to the three-factor model. This result is also theoretically justifiable. Compared to the 12-item version, GHQ-20 provides additional fourth factor of anhedonia, suggesting some discriminative power.