应用项目反应理论创建图形推理测验题库

自编235个图形推理测验题目。采用铆测验等值设计,以72个联合型瑞文测验题目为铆题,对初中到大学各能力层次的1733名男性进行了测验。使用BILOG MG3.0（边际极大似然估计）对实测数据进行了分析,采用Logsitic 3参数模型。剔除数据与模型拟合不好的题目以及信息函数最大值小于0.3的题目,最终建立一个包含181道题目的题库。该题库可以用于淘汰智力较低的应征青年     

小学生图形推理策略个体差异

选取一至六年级儿童145名为对象,根据项目中图形关系的规则,把瑞文测验的项目分成6类,选择出14道题目为实验材料,探讨小学生图形推理策略的个体差异.结果发现,数学能力不同的小学生在解决简单图形推理问题时,基本上使用知觉算法策略,没有表现出差异.但在较难图形推理问题时差异显著,中高数学水平儿童主要使用分析策略和知觉分析策略;而低数学水平儿童基本上使用知觉匹配策略;除了格式塔类型的题目以外,推理水平高的儿童在解决这五类题目时主要使用分析策略和知觉分析策略,而推理水平低的儿童主要使用知觉匹配策略;推理水平高的儿童在解决较为简单的图形推理问题时的策略使用很集中,随着题目难度的加大,策略变得越来越分散,而推理水平低的儿童则无论题目难易如何变化,他们的策略主要使用知觉匹配策略,而且表现出随机性特点.     

矩阵完成问题的项目生成研究

依据Embretson提出的认知设计系统方法,设计并编制了矩阵完成问题的项目生成系统,实际生成了矩阵完成问题测验。探讨矩阵测验与瑞文测验的关系,以及认知模型对矩阵问题的难度和区分度的预测能力。结果表明所设计的认知模型对矩阵项目的性能参数有一定的预测能力,生成的矩阵测验与瑞文测验有基本相同的心理测量属性。可以使用该系统生成的矩阵项目来测量被试的抽象推理能力。     

我国一大型考试等值的铆题参数漂移检验

设置铆题来链接不同测验形式是一种常用的等值设计。但受到曝光等因素影响,铆题功能在不同施测时间会发生改变。本研究采用MH检验和logistic回归考察我国一大型考试等值的铆题质量,结果发现,有22个铆题发生参数漂移,铆题的难度参数和区分度参数可能发生漂移;这些铆题中大部分在二次使用时无法通过模型拟合检验;若不删除参数发生漂移的铆题导致较大的系统等值误差,应将铆题参数漂移检验作为等值中的一步必要工作。     

无铆题情况下测验分数等值方法探索——构造铆测验法

研究旨在探索无铆题情况下,使用构造铆测验法,实现测验分数等值。研究一和研究二分别探索题目难度排序错误、铆题难度差异对构造铆测验法的影响。结果表明：（1）等组条件下,随着错误铆题比例,难度排序错误程度,铆题难度差异增大,构造铆测验法的等值误差逐渐增大,随机等组法的等值误差较为稳定;不等组条件下,构造铆测验法的等值误差均小于随机等组法;（2）对于构造铆测验法,在不等组条件下,铆测验长度越短,等值误差越大。     

铆题比例对等值精度的影响

在非等组铆测验设计中,铆题量占测验长度的多大比例比较合适,这个比例随测验长度的增大可否发生变化？这些是实际工作者和研究者非常关心的问题。该文在固定被试数和测验长度的条件下,探查铆题量所占测验长度比例（简称铆题比例）的变化对等值精度的影响,讨论了在实际等值中如何在等值精度和铆题比例之间取得平衡的问题。并在模拟研究的条件下,给出了几个反应实际等值精度的指标。     

小学生图形推理策略发展特点的研究

本研究用我们修订的瑞文推理为材料,对145名儿童图形推理策略进行研究。结果发现：小学生在解决图形推理问题时使用六种策略,它们分别是分析策略、不完全分析策略、知觉分析策略、知觉匹配策略、格式塔策略和自主想象策略;不同年龄儿童在解决不同类型题目时的策略使用表现出不同的特点,儿童在解决数量规则题中,知觉分析策略在整个小学儿童阶段占主导地位,而在解决加减规则题中,分析策略占主导地位,随年龄增长而呈上升趋势;小学二年级开始出现图形推理能力发展的飞跃,二年级儿童开始能够同时观察到两种规则,五六年级儿童更能够不受题目形式的影响．而是从本质上把握逻辑规则。     

不同铆测验设计下多维IRT等值方法的比较

实际应用中测验往往具有多维结构, 如果仍采用单维IRT方法进行等值, 会得到不准确的结果。因此对于多维结构的测验, 需要使用多维IRT等值方法来实现参数的转换。基于共同题设计, 文章通过模拟研究的方法, 考察了不同铆测验设计下几种多维IRT等值方法的表现, 同时考虑了测验长度、两个维度题目数量的比例、铆测验长度、铆测验的选择策略、两个维度之间的相关和等值群体的能力水平差异六个因素的影响。所比较的多维IRT等值方法有：均值/均值(MM)方法, 均值/标准差(MS)方法, Stoking-Lord (SL)方法, Haebara (HB)方法, 最小平方(LS)方法。结果显示：(1) SL, HB和LS方法得到的等值误差均方根最小, 且在各条件下表现较为稳定。(2) MM和MS方法在非等组条件下呈现出很大的误差均方根。(3)铆测验设计对SL, HB和LS方法的等值结果没有显著影响。(4)在两个维度之间的相关较高, 测验长度和铆测验长度较长, 等值群体的能力水平没有差异的条件下, SL, HB和LS方法得到的等值误差均方根最小。     

大学生不同认知方式对图形推理水平的影响--兼谈认知过程中的人格作用

用镶嵌图形测验方法从大学生中选出场独立性、场中间性和场依存性被试各32名．在分段限时条件下解决瑞文标准推理测验的B、C、D、E组问题。实验结果表明．认知方式不同组被试图形推理总成绩差异显著,场独立组最高、中间组次之、场依存组最低;随推理问题难度的渐增(B→C→D→E),认知方式的作用效果愈加明显,场独立组、中间组对图形类比推理(B组)、系统变化(C组)和系列关系(D组)的推理水平显著高于场依存组,对复杂抽象问题(E组)的推理水平场独立组显著高于中间组和场依存组;认知方式可解释图形推理总成绩25．9％的变异,年级可解释11．2％的变异。认知方式是影响图形推理水平的重要人格变量。     

瑞文测验项目认知难度因素分析及LLTM拟合验证

该文在以认知和测量相结合为特征的新一代测验理论的指导下,针对项目刺激特征,对影响瑞文测验项目认知难度的因素进行了分析,提取出图块繁简度、整体布局、变化维度和题序等4个因素,然后应用线性逻辑潜在特质模型（LLTM）对这四个因素进行了拟合检验,结果证明提取出的四个因素是有效的。文章还进一步探讨了研究结果在智力测验中的应用。     

项目反应理论等级反应模型项目信息量

信息函数作为项目反应理论中的一个重要概念,在进行项目和测验分析的工作中,以及在指导测验编制的工作中,有着非常重要的应用价值。信息函数的应用在计算机化自适应测验中更是重中之重,也受到最大关注。然而,关于多级记分项目信息函数特性的研究还比较少。本研究模拟了被试特质水平参数数据和项目参数数据,其中被试特质水平参数生成了121个被试特质水平参数点,项目参数生成了4批不同区分度参数数据,每批数据有126个不同难度等级参数组合模式的项目,每个项目有5个难度等级。通过数据分析后发现,等级反应模型项目提供最大信息量所对应的被试特质水平,是与该项目几个相互临近的难度等级组相适应,既不是只与其中一个难度等级对应,也不一定是与所有难度等级对应。本研究称这种规律为“临近难度等级占优”。这个发现无疑对测验质量分析和测验编制工作,包括计算机化自适应测验编制,具有重要的指导意义     

计算机自适应测验中测验安全控制方法评述

计算机自适应测验在实际应用中曾经受到了测验安全问题质疑。国内外学者主要从两种研究思路提出了测验安全控制的方法：一是控制项目的最大曝光率, 沿着这个思路发展出来的方法有SH法、项目合格方法、多重最大曝光率法等; 二是改进选题策略, 沿着这个思路发展的方法主要是 分层法及其变式。此外, 近年来出现了测验安全控制方法之间相结合的研究思路。本文从均方误差、项目曝光率、题库利用率等指标论述了测验安全控制方法的优缺点, 并概述了这些测验安全控制方法的研究发展历程与发展思路, 展望了今后的研究趋势。     

Controlling item exposure and test overlap on the fly in computerized adaptive testing

This paper proposes an on‐line version of the Sympson and Hetter procedure with test overlap control (SHT) that can provide item exposure control at both the item and test levels on the fly without iterative simulations. The on‐line procedure is similar to the SHT procedure in that exposure parameters are used for simultaneous control of item exposure rates and test overlap rate. The exposure parameters for the on‐line procedure, however, are updated sequentially on the fly, rather than through iterative simulations conducted prior to operational computerized adaptive tests (CATs). Unlike the SHT procedure, the on‐line version can control item exposure rate and test overlap rate without time‐consuming iterative simulations even when item pools or examinee populations have been changed. Moreover, the on‐line procedure was found to perform better than the SHT procedure in controlling item exposure and test overlap for examinees who take tests earlier. Compared with two other on‐line alternatives, this proposed on‐line method provided the best all‐around test security control. Thus, it would be an efficient procedure for controlling item exposure and test overlap in CATs.     

Item selection rules in a Computerized Adaptive Test for the assessment of written English

Item selection rules in a Computerized Adaptive Test for the assessment of written English. e-CAT is a Computerized Adaptive Test for the evaluation of written English knowledge, using the item selection rule most commonly employed: the maximum Fisher information criterion. Some of the problems of this criterion have a negative impact in the estimation accuracy and in the item bank security. In this study, the performance of this item selection rule is compared, by means of simulation, with two other rules: selecting the item with maximum Fisher information in an interval (Veerkamp y Berger, 1997) and a new criterion, called "maximum Fisher information in an interval with geometric mean". In general, this new rule shows smaller measurement error and smaller item overlap rates. It seems, thus, recommendable, as it allows the simultaneous improvement of estimation accuracy and the maintenance of the item bank security of e-CAT.     

Combining CAT with cognitive diagnosis: A weighted item selection approach

Computerized adaptive testing (CAT) was originally proposed to measure θ, usually a latent trait, with greater precision by sequentially selecting items according to the student’s responses to previously administered items. Although the application of CAT is promising for many educational testing programs, most of the current CAT systems were not designed to provide diagnostic information. This article discusses item selection strategies specifically tailored for cognitive diagnostic tests. Our goal is to identify an effective item selection algorithm that not only estimates θ efficiently, but also classifies the student’s knowledge status α accurately. A single-stage item selection method with a dual purpose will be introduced. The main idea is to treat diagnostic criteria as constraints: Using the maximum priority index method to meet these constraints, the CAT system is able to generate cognitive diagnostic feedback in a fairly straightforward fashion. Different priority functions are proposed. Some of them are based on certain information measures, such as Kullback–Leibler information, and others utilize only the information provided by the Q-matrix. An extensive simulation study is conducted, and the results indicate that the information-based method not only yields higher classification rates for cognitive diagnosis, but also achieves more accurate θ estimation. Other constraint controls, such as item exposure rates, are also considered for all the competing methods.     

计算机自动化项目生成概述

近年来,计算机自动化项目生成作为应对测验项目曝光问题的很具前景的一项技术,逐渐得到越来越多研究者的重视。这种技术是以认知心理学和心理测量学为基础,在测试过程中借助计算机自动生成目标难度水平的项目。该文首先简要介绍了这种技术的理论基础和两种具体方法,然后以项目设计系统法为例说明自动化项目生成研究的具体步骤与优点,最后评述了这种技术的局限性及未来的发展趋势     

自适应分组认知诊断测验设计及其选题策略

应用OMST在线装配模式,提出自适应分组认知诊断测验（CD-AMGT）。由于知识状态的先决关系是偏序关系,而且构成格（lattice),利用知识状态当前估计值在格中的上下确界对被试真实知识状态的可能范围进行界定,由此装配下一分组,分组中结合PWKL策略或SHE策略进行选题以兼顾诊断精度、效率和安全性。模拟实验表明,CD-AMGT与PWKL、SHE对比,当题目类型丰富时,以分类准确率略微降低为代价,其题库使用均匀性和计算用时均表现出较大优势。     

Investigating the relationship between item exposure and test overlap: Item sharing and item pooling

To date, exposure control procedures that are designed to control item exposure and test overlap simultaneously are based on the assumption of item sharing between pairs of examinees. However, examinees may obtain test information from more than one examinee in practice. This larger scope of information sharing needs to be taken into account in refining exposure control procedures. To control item exposure and test overlap among a group of examinees larger than two, the relationship between the two indices needs to be identified first. The purpose of this paper is to analytically derive the relationships between item exposure rate and each of the two forms of test overlap, item sharing and item pooling, for fixed‐length computerized adaptive tests. Item sharing is defined as the number of common items shared by all examinees in a group, while item pooling is the number of overlapping items that an examinee has with a group of examinees. The accuracy of the derived relationships was verified using numerical examples. The relationships derived will lay the foundation for future development of procedures to simultaneously control item exposure and item sharing or item pooling among a group of examinees larger than two.     

Predicting item exposure parameters in computerized adaptive testing

The purpose of this study is to find a formula that describes the relationship between item exposure parameters and item parameters in computerized adaptive tests by using genetic programming (GP) – a biologically inspired artificial intelligence technique. Based on the formula, item exposure parameters for new parallel item pools can be predicted without conducting additional iterative simulations. Results show that an interesting formula between item exposure parameters and item parameters in a pool can be found by using GP. The item exposure parameters predicted based on the found formula were close to those observed from the Sympson and Hetter (1985) procedure and performed well in controlling item exposure rates. Similar results were observed for the Stocking and Lewis (1998) multinomial model for item selection and the Sympson and Hetter procedure with content balancing. The proposed GP approach has provided a knowledge‐based solution for finding item exposure parameters.     

引入曝光因子的计算机化自适应测验选题策略

在计算机化自适应测验(CAT)的研究中, 制定既高效又安全的选题策略是一个追求目标。用极大项目信息量准则(MIC)选题使得测验效率高、能力估计准确, 缺点是项目调用很不均匀, 影响考试的安全; 按a分层法通过控制试题曝光率以提高考试的安全性, 但该方法可能会使测验效率略有下降, 且该方法在各层内部无法实现对区分度的调整。本文针对上述两种选题策略的优缺点, 对0-1评分下的CAT, 通过引入曝光因子、分阶段自动调整区分度的影响以及提高选题准确性等手段, 对MIC和a-STR进行改进, 引入了两类新的选题策略。计算机模拟实验显示, 新的选题方法效果比较理想。