画概念图对高中二年级学生认知结构形成的影响

运用联想测试方法探索高二学生学习新陈代谢一章后的认知结构。运用相关系数值绘制出了学生的认知结构图。结果显示,运用概念图策略进行教学的实验班学生更容易形成认知结构。实验班学生所形成的认知结构更良好、更合理。     

应聘者非言语信息对面试官评分的影响:解释、测量和控制

应聘者非言语信息是影响结构化面试中面试官准确评分的一个重要因素。社会互动理论和拟剧论从面试官角度,社会影响理论和相互依赖理论从应聘者角度分别解释了非言语信息对面试官评分的影响。对非言语信息的测量,除了传统的自陈式问卷,一些新兴的计算机识别技术也被使用。为了消除非言语信息对面试评分准确性的影响,通常会从面试前、面试中和面试后三个阶段对其进行控制。未来可以基于机器学习和大数据分析,探索非言语信息对结构化面试评分的影响,建构新的理论以解释影响过程。     

Assessment of executive function in ADHD adolescents: contribution of performance tests and rating scales

This study aimed to analyze performance on measures of neuropsychological and behavioral executive functions (EF) in adolescents with attention deficit hyperactivity disorder (ADHD), and to evaluate the utility of performance-based tests for predicting scores on behavioral EF ratings. One hundred eighteen adolescents (75 ADHD and 43 controls) aged 12–16 years performed neuropsychological tests and completed a behavior rating scale of EF. The ADHD group presented significantly lower scores than controls on Full Scale IQ (FSIQ) and all indexes of the WISC-IV, except the verbal comprehension index (VCI). The ADHD group had significantly lower scores on performance-based tests of working memory, planning and inhibition, and on EF rating scales. Scores on the cognitive EF working memory, planning and flexibility modestly predicted performance on behavioral EF. The results suggest that the combined use of performance-based tests and rating scales provides valuable complementary information that can improve the assessment of executive domains in ADHD.     

Bayesian Gaussian distributional regression models for more efficient norm estimation

A test score on a psychological test is usually expressed as a normed score, representing its position relative to test scores in a reference population. These typically depend on predictor(s) such as age. The test score distribution conditional on predictors is estimated using regression, which may need large normative samples to estimate the relationships between the predictor(s) and the distribution characteristics properly. In this study, we examine to what extent this burden can be alleviated by using prior information in the estimation of new norms with Bayesian Gaussian distributional regression. In a simulation study, we investigate to what extent this norm estimation is more efficient and how robust it is to prior model deviations. We varied the prior type, prior misspecification and sample size. In our simulated conditions, using a fixed effects prior resulted in more efficient norm estimation than a weakly informative prior as long as the prior misspecification was not age dependent. With the proposed method and reasonable prior information, the same norm precision can be achieved with a smaller normative sample, at least in empirical problems similar to our simulated conditions. This may help test developers to achieve cost-efficient high-quality norms. The method is illustrated using empirical normative data from the IDS-2 intelligence test.     

Exact tests for the rasch model via sequential importance sampling

Rasch proposed an exact conditional inference approach to testing his model but never implemented it because it involves the calculation of a complicated probability. This paper furthers Rasch’s approach by (1) providing an efficient Monte Carlo methodology for accurately approximating the required probability and (2) illustrating the usefulness of Rasch’s approach for several important testing problems through simulation studies. Our Monte Carlo methodology is shown to compare favorably to other Monte Carlo methods proposed for this problem in two respects: it is considerably faster and it provides more reliable estimates of the Monte Carlo standard error.This Research was supported in part by National Science Foundation grant DMS-0203762 and a University of Pennsylvania Research Foundation grant.The authors are grateful to Don Burdick for helpful comments. In addition, the authors wish to thank the editor, the associate editor, and the referees for their helpful suggestions.This revised article was published online in August 2005 with the PDF paginated correctly.     

Neuropsychological Differences Between Frontotemporal Dementia and Alzheimer's Disease: A Review

This paper surveys the similarities and differences between frontotemporal dementia (FTD) and Alzheimer's disease (AD). The review covers findings primarily from neuropsychological studies on memory, language, attention/executive function, and visuospatial abilities. However, neuropsychiatric and neuroimaging data are also briefly discussed. Distinguishing features of both FTD and AD are described in order to present a comprehensive clinical picture of these dementing diseases, which is essential for the process of differential diagnosis. The cause of specific cognitive deficits is also considered. Our comprehensive review of the empirical literature reveals that AD is characterized by early memory loss and visuospatial problems, while among the main features of FTD are behavioral abnormalities and executive dysfunctions.     

A data-driven approach to neuropsychological features in isolated REM behaviour disorder: A latent class analysis

Recent evidence demonstrated that neuropsychological assessment may be considered a valid marker of neurodegeneration in idiopathic REM sleep behaviour disorder (iRBD). However, little is known about the possible neuropsychological heterogeneity within the iRBD population. This retrospective study aimed to identify and describe different neuropsychological phenotypes in iRBD patients by means of a data-driven approach using latent class analysis. A total of 289 iRBD patients underwent a neuropsychological assessment evaluating cognitive domains: global cognition, language, short- and long-term memory, executive functions and visuospatial abilities. The presence of mild cognitive impairment (MCI) was also assessed. Latent class analysis was carried out to identify iRBD subtypes according to neuropsychological scores. The most parsimonious model identified three latent classes. Groups were labelled as follows: Class 2 “severely impaired” (n = 83/289): mean pathological scores in different tests, a high percentage of MCI multiple-domain and impairment in all neuropsychological domains. Class 1 “moderately impaired” (n = 44/289): mean neuropsychological score within the normal value, a high percentage of MCI (high risk to phenoconversion) and great impairment in the visuospatial domain. Class 3 “slightly impaired” (n = 162/289): no deficit worthy of attention except for short- and long-term memory. Our results suggest three different clinical phenotypes within the iRBD population. These findings may be relevant in the future for predicting the clinical trajectories of phenoconversion in iRBD.     

Compromised item detection: A Bayesian change-point perspective

Psychometric methods for accurate and timely detection of item compromise have been a long-standing topic. While Bayesian methods can incorporate prior knowledge or expert inputs as additional information for item compromise detection, they have not been employed in item compromise detection itself. The current study proposes a two-phase Bayesian change-point framework for both stationary and real-time detection of changes in each item's compromise status. In Phase I, a stationary Bayesian change-point model for compromise detection is fitted to the observed responses over a specified time-frame. The model produces parameter estimates for the change-point of each item from uncompromised to compromised, as well as structural parameters accounting for the post-change response distribution. Using the post-change model identified in Phase I, the Shiryaev procedure for sequential testing is employed in Phase II for real-time monitoring of item compromise. The proposed methods are evaluated in terms of parameter recovery, detection accuracy, and detection efficiency under various simulation conditions and in a real data example. The proposed method also showed superior detection accuracy and efficiency compared to the cumulative sum procedure.     

标准参照测验中的信度估计公式

标准参照测验是与常模参照测验不同的一种测验,在标准参照测验中,一个人在测验上的分数不是和他人相比较而是和某个已经设定的标准作比较。如果测验是从某功课论域中随机抽样构造而成,则使用者希望知道考生在这份测验上的观测分数与其在该功课论域上的分数（假如已知）的接近程度;如果使用者想根据测验分数对考生作掌握分类,则他们关心这个推断与假设考生论域分数已知时所作推断一致程度有多高。本文对这两个问题的信度估计进行探讨,得到几个有用的估计公式。     

Linked arguments and the validity requirement

In this paper I demonstrate that most textbook accounts of the linked/convergent distinction fail to conform to the widespread intuition that all valid arguments ought to be classified as linked arguments. I also show that standard textbook accounts of linkage and convergence cannot provide a satisfactory treatment of fallacies of irrelevance and, due to their general insensitivity to the epistemic context in which arguments are offered, must be supplemented by subjective accounts of linkage and convergence which appeal exclusively to authorial beliefs and intentions.Drafts of this paper were read at the Ontario Philosophical Society meeting held at Trent University in October 1990 and the Central Division meeting of the American Philosophical Association held in Chicago in April 1991. I thank Trudy Govier, Hans Hansen and an anonymous referee for helpful and encouraging comments on various drafts.