Cognitive control and word recognition speed influence the Stroop effect in bilinguals

Bilinguals have been shown to be less susceptible to Stroop interference in their first language than monolinguals, though the cause is currently being debated. In two experiments, we explored how cognitive control and word recognition contribute to the Stroop effect by contrasting cognitive control (via a Simon arrow task), word recognition speed (via a Chinese/English word recognition task) and Stroop susceptibility (via a verbal Stroop task) between proficient and non‐proficient Chinese–English bilinguals. Compared to non‐proficient bilinguals, proficient bilinguals showed better cognitive control at inhibiting irrelevant information, and they were slower at recognising Chinese words but quicker at recognising English words. Critically, we also showed that proficient bilinguals showed a smaller Stroop effect than non‐proficient bilinguals in Chinese but a comparable Stroop effect as non‐proficient bilinguals in English. The results cannot be accounted for by cognitive control or word recognition speed alone; instead, they are best accommodated by assuming that cognitive control and word recognition speed jointly determine the Stroop effect. Thus, we conclude that enhanced cognitive control and delayed word recognition combine to reduce Stroop effect in bilinguals as compared to monolinguals.     

Maximum Marginal Likelihood Estimation of a Monotonic Polynomial Generalized Partial Credit Model with Applications to Multiple Group Analysis

We present a semi-parametric approach to estimating item response functions (IRF) useful when the true IRF does not strictly follow commonly used functions. Our approach replaces the linear predictor of the generalized partial credit model with a monotonic polynomial. The model includes the regular generalized partial credit model at the lowest order polynomial. Our approach extends Liang’s (A semi-parametric approach to estimate IRFs, Unpublished doctoral dissertation, 2007) method for dichotomous item responses to the case of polytomous data. Furthermore, item parameter estimation is implemented with maximum marginal likelihood using the Bock–Aitkin EM algorithm, thereby facilitating multiple group analyses useful in operational settings. Our approach is demonstrated on both educational and psychological data. We present simulation results comparing our approach to more standard IRF estimation approaches and other non-parametric and semi-parametric alternatives.     

Limited‐information goodness‐of‐fit testing of diagnostic classification item response models

Despite the growing popularity of diagnostic classification models (e.g., Rupp et al., 2010, Diagnostic measurement: theory, methods, and applications, Guilford Press, New York, NY) in educational and psychological measurement, methods for testing their absolute goodness of fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full‐information test statistics such as Pearson's X² and the likelihood ratio statistic G² suffer from sparseness in the underlying contingency table from which they are computed. Recently, limited‐information fit statistics such as Maydeu‐Olivares and Joe's (2006, Psychometrika, 71, 713) M₂ have been found to be quite useful in testing the overall goodness of fit of item response theory models. In this study, we applied Maydeu‐Olivares and Joe's (2006, Psychometrika, 71, 713) M₂ statistic to diagnostic classification models. Through a series of simulation studies, we found that M₂ is well calibrated across a wide range of diagnostic model structures and was sensitive to certain misspecifications of the item model (e.g., fitting disjunctive models to data generated according to a conjunctive model), errors in the Q‐matrix (adding or omitting paths, omitting a latent variable), and violations of local item independence due to unmodelled testlet effects. On the other hand, M₂ was largely insensitive to misspecifications in the distribution of higher‐order latent dimensions and to the specification of an extraneous attribute. To complement the analyses of the overall model goodness of fit using M₂, we investigated the utility of the Chen and Thissen (1997, J. Educ. Behav. Stat., 22, 265) local dependence statistic $X_{\mathrm{LD}}^2$ for characterizing sources of misfit, an important aspect of model appraisal often overlooked in favour of overall statements. The $X_{\mathrm{LD}}^2$ statistic was found to be slightly conservative (with Type I error rates consistently below the nominal level) but still useful in pinpointing the sources of misfit. Patterns of local dependence arising due to specific model misspecifications are illustrated. Finally, we used the M₂ and $X_{\mathrm{LD}}^2$ statistics to evaluate a diagnostic model fit to data from the Trends in Mathematics and Science Study, drawing upon analyses previously conducted by Lee et al., (2011, IJT, 11, 144).     

Coh-metrix: analysis of text on cohesion and language.

Advances in computational linguistics and discourse processing have made it possible to automate many language- and text-processing mechanisms. We have developed a computer tool called Coh-Metrix, which analyzes texts on over 200 measures of cohesion, language, and readability. Its modules use lexicons, part-of-speech classifiers, syntactic parsers, templates, corpora, latent semantic analysis, and other components that are widely used in computational linguistics. After the user enters an English text, CohMetrix returns measures requested by the user. In addition, a facility allows the user to store the results of these analyses in data files (such as Text, Excel, and SPSS). Standard text readability formulas scale texts on difficulty by relying on word length and sentence length, whereas Coh-Metrix is sensitive to cohesion relations, world knowledge, and language and discourse characteristics.     

The Trajectory of Counseling in China: Past,Present, and Future Trends

This article surveys the past, present, and future trends of counseling in China. Historically, mental health problems were addressed within the family. Currently, psychotherapy from trained practitioners is available on a limited basis, at least in urban settings. The challenge of mental health in China is tremendous, and the efforts to meet that challenge are encouraging. The authors recommend that in the future, prevention and intervention services be offered that are ecosystemic, strengths‐based, and culturally appropriate.     

Role of Surface Roughness in Hysteresis during Adhesive Elastic Contact

In experiments that involve contact with adhesion between two surfaces, as found in atomic force microscopy or nanoindentation, two distinct contact force (P) vs. indentation-depth (h) curves are often measured depending on whether the indenter moves towards or away from the sample. The origin of this hysteresis is not well understood and is often attributed to moisture, plasticity or viscoelasticity. Here we report experiments that show that hysteresis can exist in the absence of these effects, and that its magnitude depends on surface roughness. We develop a theoretical model in which the hysteresis appears as the result of a series of surface instabilities, in which the contact area grows or recedes by a finite amount. The model can be used to estimate material properties from contact experiments even when the measured P-h curves are not unique.     

A Two-Tier Full-Information Item Factor Analysis Model with Applications

Motivated by Gibbons et al.’s (Appl. Psychol. Meas. 31:4–19, 2007) full-information maximum marginal likelihood item bifactor analysis for polytomous data, and Rijmen, Vansteelandt, and De Boeck’s (Psychometrika 73:167–182, 2008) work on constructing computationally efficient estimation algorithms for latent variable models, a two-tier item factor analysis model is developed in this research. The modeling framework subsumes standard multidimensional IRT models, bifactor IRT models, and testlet response theory models as special cases. Features of the model lead to a reduction in the dimensionality of the latent variable space, and consequently significant computational savings. An EM algorithm for full-information maximum marginal likelihood estimation is developed. Simulations and real data demonstrations confirm the accuracy and efficiency of the proposed methods. Three real data sets from a large-scale educational assessment, a longitudinal public health survey, and a scale development study measuring patient reported quality of life outcomes are analyzed as illustrations of the model’s broad range of applicability.     

语言耗损研究述评

本文概述语言耗损研究的历史与现状,包括语言耗损研究的主要内容和意义,以及目前存在的若干问题和难点。作者强调指出,语言耗损乃语言习得的伴生产物,关系极其密切．研究习得决不能忽视研究耗损。此外,由于环境因素对语言耗损有重要影响以及非同源语言对语言习得具有负面作用,研究汉语语言环境下外语耗损对中国的外语教学具有特殊的重要意义。     

父母婚姻质量、协同教养对青少年问题行为的影响:同时或者滞后溢出?

采用父母婚姻质量、协同教养和SDQ问卷,对416名初中生进行6个月的追踪测试,考察父母婚姻质量与协同教养之间的溢出效应及其对青少年问题行为的影响。结果发现：（1）父母婚姻质量与协同教养之间不仅存在同时溢出效应,而且存在滞后溢出效应;（2）在同一时间段内,父亲婚姻质量通过父亲团结性协同教养对青少年问题行为具有负向预测作用;（3）母亲婚姻质量不仅在同一时间段内,而且在不同时间段内通过母亲的冲突性、贬低性协同教养对青少年问题行为具有正向预测作用。因此,父母婚姻质量通过协同教养对青少年问题行为起着长期的、重要的影响。