The role of structural consistency between categories and attributes in hierarchical category learning

This study investigated how consistency between categories and attributes determines attribute selection in hierarchical category learning. Participants learned six categories for which number and color were equally relevant attributes, followed by a transfer task, to test which attribute was used. Before that, half of them learned embedding higher-level categories for which numbers were likely to be used. Orthogonal to this factor, the hierarchical structure was made explicit for half of them by category labels. The results showed that participants used numbers in the prior learning, but that the use of numbers was inhibited in the subsequent six-category learning task. However, this inhibitory effect was reduced when the hierarchical structure was explicit. The pattern of results suggests that attribute selection is determined by structural consistency between categories and attributes, not by a prior use of an attribute.     

四种新的基于属性平衡的CD-CAT选题策略开发研究

基于属性平衡的CD-CAT选题策略能够保证每个认知属性被相当数量的题目测量,从而提高被试属性判准率,传统的基于属性平衡的选题策略包括MMGDI法和MGCDI法。本文针对传统的基于属性测量次数平衡选题策略进行改进,提出4种新的基于属性平衡的选题策略：RMGDI、RMCDI、SE-RMGDI、SE-RMCDI,前两种为基于属性测量次数平衡,后两种为基于属性测量精度平衡的选题策略。模拟研究表明：（1）定长CD-CAT条件下,短测验中,MMGDI表现最好,而长测验中,SE-RMGDI和SE-RMCDI的表现优于传统的属性平衡选题策略。（2）不定长CD-CAT条件下,RMGDI在判准率指标上表现优于传统的属性平衡选题策略,4种新的属性平衡策略在测量效率和综合指标上的表现均优于传统的选题策略。     

Numerical and verbal decision analysis: comparison on practical cases

Numerical decision analysis (NDA), derived from statistical decision theory, is very well known. Verbal decision analysis (VDA), oriented towards so‐called unstructured problems, where the qualitative and uncertain factors dominate, is a newer direction in decision theory and practice. Verbal and numerical decision analyses (DAs) have been compared in an experimental setting, with groups of students. This paper presents the results of a comparison in the context of live practical tasks. Both approaches were attempted on two comparable choices, facing both Russian and US government agencies, involving a choice between oil and gas transportation options. The resulting methodological insights are generalized into a systematic comparison of the strong and weak features of each approach. Copyright © 2000 John Wiley & Sons, Ltd.     

Differential weighting in choice versus advice: I’ll do this,you do that

We propose that when individuals make a decision for themselves they weight attributes more uniformly compared to when they give advice. In Study 1, 138 participants were given a hypothetical choice between two jobs varying on two dimensions and asked either to choose for themselves, offer advice to a best friend, or offer advice to an acquaintance. We hypothesized that respondents offering advice would favor the option with the higher value on the more important dimension. More participants in the acquaintance condition recommended the job with a higher value on the important dimension than participants making the choice for themselves. Study 2 (N=62) tested the hypothesis in a situation where the options consisted of three dimensions. One option was relatively high on two of the three dimensions and the other option was relatively high on the remaining ‘socially important’, or ‘prominent’, dimension. The uniform weighting hypothesis for self‐choice predicts higher frequency of choice for the former option. Data were consistent with this prediction. Study 3 (N=170) tested the hypothesis in students' choice of major at the university. We made use of an actual event, a pending university budget cut, that would require some students to change majors. Participants either made the decision for themselves, made a recommendation to a student in their same department, or made a recommendation to a student in another department facing the analogous dilemma. Replicating the findings of the first two studies, participants offering advice to a student in another department suggested staying with their current major significantly more than participants making the choice for themselves. Copyright © 1999 John Wiley & Sons, Ltd.     

Loglinear multidimensional IRT models for polytomously scored items

A loglinear IRT model is proposed that relates polytomously scored item responses to a multidimensional latent space. The analyst may specify a response function for each response, indicating which latent abilities are necessary to arrive at that response. Each item may have a different number of response categories, so that free response items are more easily analyzed. Conditional maximum likelihood estimates are derived and the models may be tested generally or against alternative loglinear IRT models.Hank Kelderman is currently affiliated with Vrije Universiteit, Amsterdam.We thank Linda Vodegel-Matzen of the Division of Developmental Psychology of the University of Amsterdam for making available the data used in the example in this article.     

选项数量和属性重要性对决策中信息加工的影响

本研究采用决策过程研究方法中的信息板技术,以现实生活中的职业选择作为决策任务,考察了选项数量和选项属性的重要性对决策过程中信息加工的影响方式。结果表明:选项数量对决策过程的信息搜索深度、搜索模式和策略的补偿性产生了影响;选项属性的重要性并不影响决策者对属性的查看时间,但影响了决策者对属性的点击次数。     

The Two-Sense Reading of Spinoza’s definition of attribute

Spinoza’s definition of ‘attribute’ (E1d4) has been described as ‘one of the most puzzling passages in the Ethics’ and ‘a longstanding worry’ for Spinoza interpreters. Its puzzling status stems from (a) its apparent ‘subjectivist’ character and (b) the dominant understanding of Spinoza’s notion of attribute as an ‘objectivist’ notion. The paper aspires to remove this puzzlement by proposing and defending a reading of E1d4 in which it is understood to have two senses. First, I defend the objectivist character of Spinoza’s notion of attribute, and explain why E1d4 is problematic within the framework of an objectivist interpretation of the Spinozistic attribute. Second, I propose a reading of E1d4 as having two senses and explain the cause of an apparent contradiction in E1d4. Finally, I devote the largest part of the paper to a defence of the Two-Sense Reading of E1d4. More specifically, I draw on four sources for this defence: (a) the structure of E1d1 and E1d3, (b) the content and form of E1p4 and its demonstration, (c) Spinoza’s doctrine of parallelism and (d) Descartes’ treatment of attribute and its influence on Spinoza.     

基于等级反应模型的属性层级方法

给出基于等级反应模型的属性层级方法（Attribute Hierarchy Method, AHM）,并简记为GRM-AHM,提出了相应的确定GRM-AHM的期望项目反应模式全集的方法和一种新的归类法LL。用蒙特卡洛模拟实验比较GRM-AHM的几种归类法的归准率（属性模式归准率和单个属性的平均判准率）。结果发现,新归类法的归准率与AHM中的方法A差不多,但比方法B高很多;随着被试作答失误率的提高,它们的归准率都有所下降。在归类精度和简单性方面,GRM-AHM都比Bolt等(2004)提出的多级评分融合模型（Fusion Model）好     

Do learned irrelevance and perseveration play a role during discrimination learning?

In both healthy participants and various patient populations, performance on attentional set-shifting tasks has been found to be affected by learned irrelevance and/or perseveration. The present study examined whether or not these processes also play a role during the initial discrimination learning phase of those tasks. To this end, participants first solved a multidimensional discrimination learning task. Thereafter, they underwent three types of shift of relevant and/or irrelevant stimulus attributes, which enabled the assessment of the separate contribution of perseveration and learned irrelevance to post-shift task performance. Subsequent correlational analyses revealed that the number of errors during initial discrimination learning was significantly correlated with the number of errors in the learned irrelevance-shift but not the perseveration-shift. This suggests that processes underlying learned irrelevance in post-shift task performance also play a significant role during initial discrimination learning. The implications of these results for interpreting deficits in shifting are discussed.