同声传译过程中的工作记忆与双语控制研究

同声传译是一项受时间限制的高度复杂的双语活动,译员在接收原语输入的同时要进行译入语输出。同传中译员要经过原语接收、理解、转换、译入语表达等一系列过程。近年来有研究者开始尝试同声传译过程中的工作记忆研究,认为工作记忆是同传作业的关键因素,并提出工作记忆在同传中的扩展模型。本文主要就同声传译的关键特征与多任务处理模型、工作记忆在同传中的作用机制和译入语提取时的双语控制机制等问题进行简要介绍,并提出了进一步的研究思路。     

相似性词汇同时性加工与相继性加工的比较

为考查同时性学习与相继性学习在相似性材料学习中的特点,本研究以57名大学一年级学生为被试,用英语单词记忆测验考查了相似性英语新单词的同时性学习和相继性学习的差异。结果发现,对于相似性英语新单词来说,同时性学习的效果明显优于相继性学习效果。这表明,两种不同的学习方式在信息处理过程和信息加工水平上存在不同。     

ACQUISITION OF EXPRESSIVE SIGNING BY AUTISTIC CHILDREN: AN EVALUATION OF THE RELATIVE EFFECTS OF SIMULTANEOUS COMMUNICATION AND SIGN-ALONE TRAINING

Two methods of training autistic children to use manual signs were compared. Two children, one mute and one capable of some verbal imitation, were taught to use signs as expressive labels for pictures of objects. Using an alternating treatments design, speed of sign acquisition was compared across two training conditions in which signs were presented either accompanied by, or without, the corresponding verbal label. In both conditions, the training procedure incorporated reinforcement, modeling, prompting, fading, and stimulus rotation. The efficacy of training in both treatment conditions was demonstrated by the use of a multiple baseline control across signs, but no clear differences in acquisition speed across conditions were apparent. Posttests conducted to assess stimulus control of signing, and learning of verbal labels when these were present in training, showed that the behavior of the imitative, but not the mute, child was controlled by the verbal stimuli. The implications of the results both for understanding deficits characteristic of autistic children and for developing appropriate language training procedures are discussed.     

Linear structural equations with latent variables

An interdependent multivariate linear relations model based on manifest, measured variables as well as unmeasured and unmeasurable latent variables is developed. The latent variables include primary or residual common factors of any order as well as unique factors. The model has a simpler parametric structure than previous models, but it is designed to accommodate a wider range of applications via its structural equations, mean structure, covariance structure, and constraints on parameters. The parameters of the model may be estimated by gradient and quasi-Newton methods, or a Gauss-Newton algorithm that obtains least-squares, generalized least-squares, or maximum likelihood estimates. Large sample standard errors and goodness of fit tests are provided. The approach is illustrated by a test theory model and a longitudinal study of intelligence.This investigation was supported in part by a Research Scientist Development Award (KO2-DA00017) and a research grant (DA01070) from the U. S. Public Health Service.     

Principal component analysis of three-mode data by means of alternating least squares algorithms

A new method to estimate the parameters of Tucker's three-mode principal component model is discussed, and the convergence properties of the alternating least squares algorithm to solve the estimation problem are considered. A special case of the general Tucker model, in which the principal component analysis is only performed over two of the three modes is briefly outlined as well. The Miller & Nicely data on the confusion of English consonants are used to illustrate the programs TUCKALS3 and TUCKALS2 which incorporate the algorithms for the two models described.     

Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units

A new methodology is proposed for the simultaneous reduction of units, variables, and occasions of a three-mode data set. Units are partitioned into a reduced number of classes, while, simultaneously, components for variables and occasions accounting for the largest common information for the classification are identified. The model is a constrained three-mode factor analysis and it can be seen as a generalization of the REDKM model proposed by De Soete and Carroll for two-mode data. The least squares fitting problem is mathematically formalized as a constrained problem in continuous and discrete variables. An iterative alternating least squares algorithm is proposed to give an efficient solution to this minimization problem in the crisp and fuzzy classification context. The performances of the proposed methodology are investigated by a simulation study comparing our model with other competing methodologies. Different procedures for starting the proposed algorithm have also been tested. A discussion of some interesting differences in the results follows. Finally, an application to real data illustrates the ability of the proposed model to provide substantive insights into the data complexities.     

Two-matrix orthogonal rotation procedures

Examples are presented in which it is either desirable or necessary to transform two sets of orthogonal axes to simple structure positions by means of the same transformation matrix. A solution is then outlined which represents a two-matrix extension of the general orthomax orthogonal rotation criterion. In certain circumstances, oblique two-matrix solutions are possible using the procedure outlined and the Harris-Kaiser [1964] logic. Finally, an illustrative example is presented in which the preceding technique is applied in the context of an inter-battery factor analysis.The work reported herein was supported by Grant S72-1886 from the Canada Council. The author acknowledges the helpful contributions of Nancy Reid and Lawrence Ward to parts of this paper.     

A model-based standardization approach that separates true bias/DIF from group ability differences and detects test bias/DTF as well as item bias/DIF

A model-based modification (SIBTEST) of the standardization index based upon a multidimensional IRT bias modeling approach is presented that detects and estimates DIF or item bias simultaneously for several items. A distinction between DIF and bias is proposed. SIBTEST detects bias/DIF without the usual Type 1 error inflation due to group target ability differences. In simulations, SIBTEST performs comparably to Mantel-Haenszel for the one item case. SIBTEST investigates bias/DIF for several items at the test score level (multiple item DIF called differential test functioning: DTF), thereby allowing the study of test bias/DIF, in particular bias/DIF amplification or cancellation and the cognitive bases for bias/DIF.This research was partially supported by Office of Naval Research Cognitive and Neural Sciences Grant N0014-90-J-1940, 4421-548 and National Science Foundation Mathematics Grant NSF-DMS-91-01436. The research reported here is collaborative in every respect and the order of authorship is alphabetical. The assistance of Hsin-hung Li and Louis Roussos in conducting the simulation studies was of great help. Discussions with Terry Ackerman, Paul Holland, and Louis Roussos were very helpful.     

数学学习困难儿童的编码加工特点:基于PASS理论的研究

同时加工和继时加工是PASS模型中的两类编码加工,二者在数学学习中发挥重要作用。使用基于PASS理论的认知评估系统（DN：CAS）单纯型数学困难、混合型数学困难和正常小学生进行两类编码加工的测评,比较研究发现,两类困难学生的两类编码加工水平均显著低于正常儿童,两类困难学生间的同时加工差异不显著,而混合型困难学生的继时加工水平显著低于单纯型困难学生。较低的同时加工水平似乎是两类数学困难的共同特征,继时加工水平的差异则似可作为单纯型与混合型困难的区分指标之一。