认知诊断计算机化自适应测验的题库使用均匀性初探

项目曝光控制是认知诊断计算机化自适应测验(CD-CAT)中亟需解决的重要问题之一。采用蒙特卡洛模拟方法对CD-CAT中五种常用选题策略(随机化方法、KL信息量方法、香农熵方法、后验加权的KL信息量方法和综合后验加权和距离加权的KL信息量方法)的题库使用情况进行探讨。结果发现:四种非随机化选题策略的题库使用均匀性较差、测验重叠率高,从而导致测验安全性较差;香农熵方法的判准率总是最高。今后可以将传统CAT中的项目曝光控制技术融入到CD-CAT选题策略中。     

单维项目因素分析：CCFA与IRT估计方法的比较

当观测指标变量为二分分类数据时,传统的因素分析方法不再适用。作者简要回顾了SEM框架下的分类数据因素分析模型和IRT框架下的测验题目和潜在能力的关系模型,并对两种框架下主要采用的参数估计方法进行了总结。通过两个模拟研究,比较了SEM框架下GLSc和MGLSc估计方法与IRT框架下MML/EM估计方法的差异。研究结果表明：（1）三种方法中,GLSc得到参数估计的偏差最大,MGLSc和MML/EM估计方法相差不大;（2）随着样本量增大,各种项目参数估计的精度均提高;（3）项目因素载荷和难度估计的精度受测验长度的影响;（4）项目因素载荷和区分度估计的精度受总体因素载荷（区分度）高低的影响;（5）测验项目中阈值的分布会影响参数估计的精度,其中受影响最大的是项目区分度。（6）总体来看,SEM框架下的项目参数估计精度较IRT框架下项目参数估计的精度高。此外,文章还将两种方法在实际应用中应该注意的问题提供了一些建议。     

个人自立、反馈对长时距估计的影响

为了探索人格与反馈对时间估计的影响,本研究采用非时间任务和预期式时距估计的方法对个人自立高分组与低分组共40名被试进行了研究。结果发现：（1）虽然差异不显著,但是在两次时距估计中个人自立高分组的时距估计绝对错误量均小于低分组;（2）个人自立高分组的时距估计绝对错误量变化幅度显著小于低分组;（3）个人自立高分组在两次时距估计绝对错误量上的相关明显大于低分组;（4）有反馈组的时距估计绝对错误量显著小于无反馈组。据此可以认为：（1）由个人自立导致的时间估计的个体差异表现在时间估计的误差变异度和准确性两个方面。高个人自立者的时间估计误差的变异度更小,同时可能倾向于更准确地进行时距估计。（2）反馈有助于提高时间估计的准确性。（3）“绝对错误量变化幅度”和“时距估计绝对错误量的相关”是两个值得在今后的研究中应用的指标。     

Overestimation and contraction biases of depth information stored in working memory depend on spatial configuration

Depth perception is essential for effective interaction with the environment. Although the accuracy of depth perception has been studied extensively, it is unclear how accurate the depth information is stored in working memory. In this study, we investigated the accuracy and systematic biases of depth representation by a delayed estimation task. The memory array consisted of items presented at various stereoscopic depth positions, and the participants were instructed to estimate the depth position of one target item after a retention interval. We examined the effect of spatial configuration by comparing the memory performance in the whole-display condition where non-target memory items were present during retrieval with that in the single-display condition where non-target memory items were absent. In the single-display condition, we found an overestimation bias that the depth estimates were farther than the corresponding depth positions defined by disparity, and a contraction bias that the stored depth positions near the observer were overestimated and those far from the observer were underestimated. The magnitude of these biases increased with the number of to-be-stored items. However, in the whole-display condition, the overestimation bias was corrected and the contraction bias did not increase with the number of to-be-stored items. Our findings suggested that the number of to-be-stored items could affect the accuracy of depth working memory, and its effect depended crucially on whether the information of spatial configuration of memory display was available at the retrieval stage.     

结合题目作答时间的计算机化自适应测验选题方法

计算机形式的测验能够记录考生在测验中的题目作答时间（Response Time, RT），作为一种重要的辅助信息来源，RT对于测验开发和管理具有重要的价值，特别是在计算机化自适应测验（Computerized Adaptive Testing, CAT）领域。本文简要介绍了RT在CAT选题方面应用并作以简评，分析了这些技术在实践中的可行性。最后，探讨了当前RT应用于CAT选题存在的问题以及可以进一步开展的研究方向。     

Resolving the paradox of the active user: stable suboptimal performance in interactive tasks

This paper brings the intellectual tools of cognitive science to bear on resolving the “paradox of the active user” [Interfacing Thought: Cognitive Aspects of Human-Computer Interaction, Cambridge, MIT Press, MA, USA]—the persistent use of inefficient procedures in interactive tasks by experienced or even expert users when demonstrably more efficient procedures exist. The goal of this paper is to understand the roots of this paradox by finding regularities in these inefficient procedures. We examine three very different data sets. For each data set, we first satisfy ourselves that the preferred procedures used by some subjects are indeed less efficient than the recommended procedures. We then amass evidence, for each set, and conclude that when a preferred procedure is used instead of a more efficient, recommended procedure, the preferred procedure tends to have two major characteristics: (1) the preferred procedure is a well-practiced, generic procedure that is applicable either within the same task environment in different contexts or across different task environments, and (2) the preferred procedure is composed of interactive components that bring fast, incremental feedback on the external problem states. The support amassed for these characteristics leads to a new understanding of the paradox. In interactive tasks, people are biased towards the use of general procedures that start with interactive actions. These actions require much less cognitive effort as each action results in an immediate change to the external display that, in turn, cues the next action. Unfortunately for the users, the bias to use interactive unit tasks leads to a path that requires more effort in the long run. Our data suggest that interactive behavior is composed of a series of distributed choices; that is, people seldom make a once-and-for-all decision on procedures. This series of biased selection of interactive unit tasks often leads to a stable suboptimal level of performance.     

Children acquire the later‐greater principle after the cardinal principle

Many have proposed that the acquisition of the cardinal principle (CP) is a result of the discovery of the numerical significance of the order of the number words in the count list. However, this need not be the case. Indeed, the CP does not state anything about the numerical significance of the order of the number words. It only states that the last word of a correct count denotes the numerosity of the counted set. Here, we test whether the acquisition of the CP involves the discovery of the later‐greater principle – that is, that the order of the number words corresponds to the relative size of the numerosities they denote. Specifically, we tested knowledge of verbal numerical comparisons (e.g., Is ‘ten’ more than ‘six’?) in children who had recently learned the CP. We find that these children can compare number words between ‘six’ and ‘ten’ only if they have mapped them onto non‐verbal representations of numerosity. We suggest that this means that the acquisition of the CP does not involve the discovery of the correspondence between the order of the number words and the relative size of the numerosities they denote.     

Audiovisual time-to-collision estimation for accelerating vehicles: The acoustic signature of electric vehicles impairs pedestrians' judgments

To avoid collisions, pedestrians intending to cross a road need to accurately estimate the time-to-collision (TTC) of an approaching vehicle. For TTC estimation, auditory information can be considered particularly relevant when the approaching vehicle accelerates. The sound of vehicles with internal combustion engine (ICEVs) provides characteristic auditory information about the acceleration state (increasing rotational speed and engine load). However, for electric vehicles (EVs), the acoustic signature during acceleration is less salient. Although the auditory detection of EVs has been studied extensively, there is no research on potential effects of the altered acoustic signature of EVs on TTC estimation. To close this gap, we compared TTC estimates for ICEVs and for EVs with and without activated acoustic vehicle alerting system (AVAS). We implemented a novel interactive audiovisual virtual-reality system for studying the human perception of approaching vehicles. Using acoustic recordings of real vehicles as source signals, the dynamic spatial sound field corresponding to a vehicle approaching in an urban setting is generated based on physical modeling of the sound propagation between vehicle and pedestrian (listener) and is presented via sound field synthesis (higher-order Ambisonics). In addition to the auditory simulations, the scene was visually presented on a head-mounted display with head tracking. Participants estimated the TTC of vehicles that either approached at a constant speed or accelerated positively. In conditions with constant speed, TTC estimates for EVs with and without AVAS were similar to those for ICEVs. In contrast, for accelerating vehicles, there was a substantial effect of the vehicle type on the TTC estimates. For the EVs, the mean TTC estimates showed a significant overestimation. Thus, subjects on average perceived the time of arrival of the EV at their position as longer than it actually was. The extent of overestimation increased with acceleration and presented TTC. This pattern is similar to a first-order TTC estimation representing a failure to consider the acceleration, which is consistently reported in the literature for visual-only presentations of accelerating objects. In comparison, the overestimation of TTC was largely reduced for the accelerating ICEVs. The AVAS somewhat improved the TTC estimates for the accelerating EVs, but without reaching the same level of accuracy as for the ICEVs. In real traffic scenarios, overestimations of the TTC of approaching vehicles might lead to risky road-crossing decisions. Therefore, our finding that pedestrians are significantly less able to use the acoustic information emitted by accelerating EVs for their TTC judgments, compared to accelerating ICEVs, has important implications for road safety and for the design of AVAS technologies.     

双任务协调、任务呈现方式影响成人算术策略执行:估算证据

前人研究显示中央执行影响算术策略的执行。双任务协调作为中央执行的执行功能之一,是否会影响个体的策略执行?采用选择\无选法与改进的心理不应期范式,探讨随机/固定呈现方式下,双任务协调对算术策略执行的影响。结果表明:双任务协调影响策略执行,双反应策略执行效能显著差于单反应;任务呈现方式影响策略执行,固定方式优于随机方式;任务呈现序列影响策略执行反应时,数字先呈现的估算策略执行效能显著差于图形先呈现。总之,双任务协调、任务呈现方式影响算术策略执行,固定方式引起更明显的双任务协调代价。     

Extending adaptive world modeling by identifying and handling insufficient knowledge models

Adaptive knowledge modeling is an approach for extending the abilities of the Object-Oriented World Model, a system for representing the state of an observed real-world environment, to open-world modeling. In open environments, entities unforeseen at the design-time of a world model can occur. For coping with such circumstances, adaptive knowledge modeling is tasked with adapting the underlying knowledge model according to the environment. The approach is based on quantitative measures, introduced previously, for rating the quality of knowledge models. In this contribution, adaptive knowledge modeling is extended by measures for detecting the need for model adaptation and identifying the potential starting points of necessary model change as well as by an approach for applying such change. Being an extended and more detailed version of [17], the contribution also provides background information on the architecture of the Object-Oriented World Model and on the principles of adaptive knowledge modeling, as well as examination results for the proposed methods. In addition, a more complex scenario is used to evaluate the overall approach.