内隐学习中的知识习得及其无意识性测量*

本研究采用经典的人工语法范式,并引入迁移任务探讨在记忆和规则探索两种指导语条件下,被试所习得的究竟是规则还是组块？同时采用结构知识主观测量的方法,对内隐学习习得知识的无意识性进行测量。结果发现记忆指导语条件下的被试能成功区分合法串和非法串,即出现语法学习效应,但规则探索指导语条件下的被试并没有表现出语法或组块学习效应,结构知识的主观测量发现这种内隐学习的优势效应主要来自无意识结构知识的贡献;在迁移研究中发现附带学习组和有意学习组均在迁移任务上表现出语法学习效应,这表明在人工语法学习中所获得的语法规则是抽象的和可迁移的。     

Evaluating Cognitive Training Outcomes: Validity and Utility of Structural Knowledge Assessment

Conventional approaches to evaluating cognitive outcomes of training typically use paper-and-pencil tests that emphasize gains or differences in declarative knowledge. Yet a key factor in differentiating expert and novice performance is the way individuals organize their knowledge. Accordingly, the acquisition of meaningful knowledge structures and methods of assessing structural knowledge are potentially important issues for designing and evaluating training programs. Two studies were conducted to examine the validity and utility of one structural assessment technique called Pathfinder (Schvaneveldt, Durso, & Dearholt, 1989). Results from academic and organizational samples indicated that Pathfinder measures of structural knowledge quality predicted individual differences in performance self-efficacy. After controlling for differences in declarative knowledge, measures of structural knowledge quality added to the prediction of performance self-efficacy in the student sample, but not in the organizational sample. The unique features and potential advantages of structural assessment for training evaluation are discussed.     

团体认知影响数学概念结构表征的实验研究

概念结构表征一直是认知心理学研究的重要内容。本研究以团体及表征理论为基础,通过设计不同的团体认知条什来研究认知交互作用对概念结构表征的影响。实验结果表明不同的团体认知表现出了不同的认知交互,对概念结构表征也产生了不同的影响。     

社会称许性量表的测量等价性探讨

若观测变量和潜在特质之间的关系在相比较的群体之间等同,就称该量表具备测量等价性。测量工具满足测量等价性的要求是进行组间差异比较的前提条件。该文首先明确测量等价性的概念及在结构方程模型中所要满足的5个条件,然后以社会称许性的性别差异为例,阐述测量等价性检验和建立的方法。结果表明,男性群体和女性群体的测量等价。文章最后讨论了该研究的理论意义和不足之处。     

A Multilevel Contextual Model of Family Conflict and Deviance

This paper presents a multiple-group multivariate hierarchical specification of family problem behaviors across ethnicities using structural equation modeling techniques which explicitly model the individual-level and family-level covariance matrices in familial problem behavior. Analyses were conducted across White and African American ethnic groups. The sample (N = 1,168; 647 White and 521 African Americans) comprised children and their parents from 392 families. In addition to relations between family conflict and deviant behaviors, covariates were included at each level of analysis: neighborhood desirability at the family (between) level, and age and gender at the individual (within) level. At the between level, neighborhood desirability influenced family conflict and family conflict influenced family levels of deviance. At the within level, conflict was significantly related to individual levels of deviance. Discussion focuses on the substantive results as well as the application of multilevel analyses to contextual influences of family problem behavior.     

Reliability Beyond Theory and Into Practice

The critical reactions of Bentler (2009, doi:), Green and Yang (2009a, doi:; 2009b, doi:), and Revelle and Zinbarg (2009, doi:) to Sijtsma’s (2009, doi:) paper on Cronbach’s alpha are addressed. The dissemination of psychometric knowledge among substantive researchers is discussed.     

Structural equation models with continuous and polytomous variables

A two-stage procedure is developed for analyzing structural equation models with continuous and polytomous variables. At the first stage, the maximum likelihood estimates of the thresholds, polychoric covariances and variances, and polyserial covariances are simultaneously obtained with the help of an appropriate transformation that significantly simplifies the computation. An asymptotic covariance matrix of the estiates is also computed. At the second stage, the parameters in the structural covariance model are obtained via the generalized least squares approach. Basic statistical properties of the estimates are derived and some illustrative examples and a small simulation study are reported.This research was supported in part by a research grant DA01070 from the U. S. Public Health Service. We are indebted to several referees and the editor for very valuable comments and suggestions for improvement of this paper. The computing assistance of King-Hong Leung and Man-Lai Tang is also gratefully acknowledged.     

Parameterizing inequality constraints on unique variances in linear structural models

Current computer programs for analyzing linear structural models will apparently handle only two types of constraints: fixed parameters, and equality of parameters. An important constraint not handled is inequality; this is particularly crucial for preventing negative variance estimates. In this paper, a method is described for imposing several kinds of inequality constraints in models, without the necessity for having computer programs which explicitly allow such constraints. The examples discussed include the prevention of Heywood cases, extension to inequalities of parameters to be greater than a specified value, and imposing ordered inequalities. Work on this project was aided by the City University of New York—Professional Staff Congress Research Award Program Grant Number 13631.     

Interpreting the WPPSI subtests scores of language impaired children--a structural approach

The problem of characterising more specifically the cognitive requirements involved in subtests from standardised measures of intelligence represents a main problem in the research on exceptional populations. Seventy-five specifically language impaired (SLI) preschool children and 49 normally developing children were administered the Wechsler Preschool and Primary Scale of Intelligence (WPPSI). The scaled scores on the WPPSI were categorised according to Bannatyne's suggested regrouping to determine whether the pattern Spatial > Conceptual > Sequential could be observed in the data. The predicted pattern was only partially confirmed for language impaired children. The scaled scores on the WPPSI were then recategorized according to their structural complexity. Since structurally complex tasks contain more categories than the structurally simpler tasks, the pattern structurally Simple > Moderate > Complex was predicted and confirmed for language impaired children. Furthermore, it was hypothesized that the structurally Complex categories would discriminate better between language-impaired children and normally developing children than any other recoded categories. This hypothesis was confirmed. The low scores obtained by language impaired children on structurally Complex categories were interpreted as the result of capacity limitations in information processing rather than a deficit of any particular mental ability.