认知诊断计算机自适应测验中平衡属性收敛的新方法

提出两种认知诊断计算机自适应测验下平衡属性收敛的新方法（MABI、RTA）,模拟研究系统探讨和比较了此二者与已有方法（ABI、IABI和RABI）的表现。结果发现：（1）新方法较不考虑属性收敛的方法有更高的准确率以及更均衡的题目使用率;（2）新方法较ABI和RABI有稍低的准确性,但有更平衡的题目使用率;（3）新方法与IABI的准确性和题目使用率在不同选题策略下各有合优势。总之,两种新方法较好地兼顾测量准确性、题目使用率以及题库曝光情况。     

材料呈现方式对大学生分类活动影响的眼动研究

使用ASL504型眼动仪,采用2×3的混合实验设计,记录和分析24名被试在两种材料呈现方式下,对图片分类结果和分类过程中的眼动数据。结果表明:(1)大学生分类结果存在显著的呈现方式差异,但不存在显著的材料类别差异。(2)大学生在分类过程中的兴趣区数目、注视时间、注视次数、注视频率、注视点持续时间等眼动指标存在显著的呈现方式差异,但材料类别差异不显著。     

Meta‐CART: A tool to identify interactions between moderators in meta‐analysis

In the framework of meta‐analysis, moderator analysis is usually performed only univariately. When several study characteristics are available that may account for treatment effect, standard meta‐regression has difficulties in identifying interactions between them. To overcome this problem, meta‐CART has been proposed: an approach that applies classification and regression trees (CART) to identify interactions, and then subgroup meta‐analysis to test the significance of moderator effects. The previous version of meta‐CART has its shortcomings: when applying CART, the sample sizes of studies are not taken into account, and the effect sizes are dichotomized around the median value. Therefore, this article proposes new meta‐CART extensions, weighting study effect sizes by their accuracy, and using a regression tree to avoid dichotomization. In addition, new pruning rules are proposed. The performance of all versions of meta‐CART was evaluated via a Monte Carlo simulation study. The simulation results revealed that meta‐regression trees with random‐effects weights and a 0.5‐standard‐error pruning rule perform best. The required sample size for meta‐CART to achieve satisfactory performance depends on the number of study characteristics, the magnitude of the interactions, and the residual heterogeneity.     

The P600 in Implicit Artificial Grammar Learning

The suitability of the artificial grammar learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax‐related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g., subsequence familiarity) rather than the underlying syntax structure. Therefore, in this study, we controlled for the surface characteristics of the test sequences (associative chunk strength) and recorded the EEG before (baseline preference classification) and after (preference and grammaticality classification) exposure to a grammar. After exposure, a typical, centroparietal P600 effect was elicited by grammatical violations and not by unfamiliar subsequences, suggesting that the AGL P600 effect signals a response to structural irregularities. Moreover, preference and grammaticality classification showed a qualitatively similar ERP profile, strengthening the idea that the implicit structural mere‐exposure paradigm in combination with preference classification is a suitable alternative to the traditional grammaticality classification test.     

Visualising mental representations: A primer on noise-based reverse correlation in social psychology

With the introduction of the psychophysical method of reverse correlation, a holy grail of social psychology appears to be within reach – visualising mental representations. Reverse correlation is a data-driven method that yields visual proxies of mental representations, based on judgements of randomly varying stimuli. This review is a primer to an influential reverse correlation approach in which stimuli vary by applying random noise to the pixels of images. Our review suggests that the technique is an invaluable tool in the investigation of social perception (e.g., in the perception of race, gender and personality traits), with ample potential applications. However, it is unclear how these visual proxies are best interpreted. Building on advances in cognitive neuroscience, we suggest that these proxies are visual reflections of the internal representations that determine how social stimuli are perceived. In addition, we provide a tutorial on how to perform reverse correlation experiments using R.     

The On-Line Processing of Verb-Phrase Ellipsis in Aphasia

We investigate the on-line processing of verb-phrase ellipsis (VPE) constructions in two brain injured populations: Broca’s and Anomic aphasics. VPE constructions are built from two simple clauses; the first is the antecedent clause and the second is the ellipsis clause. The ellipsis clause is missing its verb and object (i.e., its verb phrase (VP)), which receives its reference from the fully specified VP in the antecedent clause. VPE constructions are unlike other sentence types that require displacement of an argument NP; these latter constructions (e.g., object-relatives, wh-questions) yield either on-time or delayed antecedent reactivation. Our results demonstrate that Anomics, like unimpaired individuals, evince reactivation of the direct object NP (within the VP) at the elided position. Broca’s patients, on the other hand, do not show reactivation of the antecedent. We consider several interpretations for our data, including explanations focusing on the larger ‘grain size’ of the reconstructed material in the ellipsis clause, the properties of the auxiliary that carries tense and agreement features, and the possibility that the cost-free syntactic copy procedure claimed to underlie VPE may be modulated by the functional deficit in Broca’s aphasia.     

Categorical invariance and structural complexity in human concept learning

An alternative account of human concept learning based on an invariance measure of the categorical stimulus is proposed. The categorical invariance model (CIM) characterizes the degree of structural complexity of a Boolean category as a function of its inherent degree of invariance and its cardinality or size. To do this we introduce a mathematical framework based on the notion of a Boolean differential operator on Boolean categories that generates the degrees of invariance (i.e., logical manifold) of the category in respect to its dimensions. Using this framework, we propose that the structural complexity of a Boolean category is indirectly proportional to its degree of categorical invariance and directly proportional to its cardinality or size. Consequently, complexity and invariance notions are formally unified to account for concept learning difficulty. Beyond developing the above unifying mathematical framework, the CIM is significant in that: (1) it precisely predicts the key learning difficulty ordering of the SHJ [Shepard, R. N., Hovland, C. L., & Jenkins, H. M. (1961). Learning and memorization of classifications. Psychological Monographs: General and Applied, 75(13), 1-42] Boolean category types consisting of three binary dimensions and four positive examples; (2) it is, in general, a good quantitative predictor of the degree of learning difficulty of a large class of categories (in particular, the 41 category types studied by Feldman [Feldman, J. (2000). Minimization of Boolean complexity in human concept learning. Nature, 407, 630-633]); (3) it is, in general, a good quantitative predictor of parity effects for this large class of categories; (4) it does all of the above without free parameters; and (5) it is cognitively plausible (e.g., cognitively tractable).     

不同历史时期谬误研究的特点

本文主要讨论了不同时期逻辑学家对逻辑谬误研究的特点。古希腊时期对谬误作出全面系统研究的是亚里士多德。亚里士多德对谬误的解决方法一般地说是经验的,没有形成一套行之有效的规则。文艺复兴时期,培根等人批判经院哲学,探讨了人类产生谬误的根源。这时期的谬误研究特点是：一是重视在归纳法的应用中产生的谬误;二是突出逻辑问题。现代逻辑学家如柯比等人则在前人的基础上,对谬误作出了更全面、更精确的分类,并且对各种谬误的解释和举例也更确切,从而使谬误理论更好地为实践服务。     

Taxicab Correspondence Analysis of Contingency Tables with One Heavyweight Column

The aim of this paper is to study the analysis of contingency tables with one heavyweight column or one heavyweight entry by taxicab correspondence analysis (TCA). Given that the mathematics of TCA is simpler than the mathematics of correspondence analysis (CA), the influence of one heavyweight column on the outputs of TCA is studied explicitly without recourse to asymptotics as done by Benzécri (Les Cahiers de L’Analyse des Données 4:413–16, 1979). A reweighting of the heavyweight column is proposed, which can also be applied to CA. A real data set is analyzed. This research is financed by NSERC of Canada. The author is grateful to the Editor, Professor B. Junker, to an Associate Editor and to three referees for their constructive comments.