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关于新课程改革中的诊断性测验研究 总被引：1，自引：0，他引：1
在新课程改革中诊断性测验正在显得越来越重要,如何进行诊断性测验是广大中小学教师面临的实际问题。规则空间模型将认知心理学和教育测量理论相结合,它首先对所要考查的属性进行梳理,并编制出包含这些属性的测验题目。然后根据学生对于题目的作答情况,将他们在规则空间中划归为不同的类别,从而诊断出各类学生的认知缺陷。 相似文献
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认知诊断通过分析被试的项目作答反应,推断被试的认知属性掌握状态,为学习困难学生设计补救教学提供了非常有价值的信息。本文作者在探讨了小学生多位数乘法计算能力的认知属性、编制了2份相同考核模式的认知诊断测验后,选择江西某小学310名高年级学生为被试,先施测第1份认知诊断测验,采用DINA模型,自编参数估计程序进行诊断,得到了每一个被试的属性掌握模式分类及全体被试在各个属性上的掌握情况。然后设计和实施补救教学,在实施补救教学后再施测第2份认知诊断测验以检验补救效果。研究发现：（1）该小学高年级学生对0XN运算法则、多位数乘以两位数的运算程序、乘法进位认知属性的掌握不太理想,特别是乘法进位。（2）属性掌握模式中属全部掌握模式的被试人数占86．47％,其余被试均分类于存在各种认知不足的掌握模式。（3）比较两份认知诊断测验报告,结果表明在认知诊断指导下的补救教学有针对性,补救后被试正确作答项目增多,属性掌握个数也有所增加,补救效果良好。 相似文献
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认知诊断作为新一代测验理论的代表,与标准测验理论在理论和应用上有着多方面的差异。本文基于认知诊断与标准测验理论的比较,阐述了认知诊断五方面的特征：（1）区别于标准测验理论中较为笼统和抽象的能力概念,以细分和具体化为特点的认知诊断属性界定;（2）区别于标准测验理论连续潜变量的认知诊断分类潜变量;（3）加入诊断指导下的补救和再评估后,认知诊断包含了周而复始的评估过程;（4）包含补救措施是否有效的认知诊断效度测量;（5）认知诊断的应用领域。文章最后指出了认知诊断目前在其发展中所存在的问题,并对该测量理论的发展进行了展望。 相似文献
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随着国内外教育测量理念的转变,传统的常模参照测验所提供的相对性评价信息已无法满足考试用户和考生的需求,标准参照测验(CriterionReferenced Test,CRT)的社会价值越来越受到重视。在对被试掌握程度进行分类决策的CRT测验中,如何确定恰当的测验长度和合格分数是影响测验分类误差的重要因素。本文在对CRT测验研究的现状、原理和用途进行考察的基础上,专门介绍了二项式概率模型在CRT测验长度决策研究中的理论和过程,并以误差控制为原则,对二项式模型在综合性标准参照语言测验长度和合格分数决策中的应用过程进行了研究。 相似文献
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规则空间模型是一种基于统计模式识别和分类的认知诊断模型,能够提供关于考生作答模式与属性掌握情况的详细信息。在理论上,该模型解决了成就测验中测验单维性与项目单维性的问题,并发展出ACC曲线对项目反应理论进行了拓展;在实践中,规则空间模型可以用于指导测验项目的编制,为诊断教学提供信息,还能广泛应用于成就测验以外的心理与教育测量的各个领域。[编者按] 相似文献
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文章使用GDINA R程序包,借助Wald检验为英语听力诊断试题中的多属性题目选出最优简约模型,组成混合模型(Mixed-CDMs)。基于Mixed-CDMs与G-DINA模型的对比分析,文章发现:在样本量不够大(N=726)的情况下,Mixed-CDMs满足模型-数据绝对拟合的较高要求,相对拟合性、人员拟合性、属性分类的可靠性以及参数估计的准确性都有所提高,且属性之间的关系更加直观易读。由此,文章验证了混合模型对于英语听力诊断测评具有适用性并有一定的应用优势,这为混合模型在英语听力测试中的应用提供了实证依据,有助于加深对英语听力认知属性关系的了解,并可为其它语言测试使用混合模型提供借鉴。 相似文献
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计算机自适应测验是现代教育测验的一种新形式。计算机自适应测验的指导理论与传统纸笔测验不同,而且测试方面有诸多的优点。本文详细介绍计算机自适应测验的基本测试流程,包括被试即时能力估计、选题策略、曝光率控制、测验终止标准等八个基本步骤;并进一步论述了计算机自适应测验在实测中应解决的关键技术与问题：在线参数估计、试题与测验交叠率控制、纸笔测验与计算机等值、多维评价与认知诊断等。 相似文献
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Most of the existing classification accuracy indices of attribute patterns lose effectiveness when the response data is absent in diagnostic testing. To handle this issue, this article proposes new indices to predict the correct classification rate of a diagnostic test before administering the test under the deterministic noise input “and” gate (DINA) model. The new indices include an item‐level expected classification accuracy (ECA) for attributes and a test‐level ECA for attributes and attribute patterns, and both of them are calculated based solely on the known item parameters and Q ‐matrix. Theoretical analysis showed that the item‐level ECA could be regarded as a measure of correct classification rates of attributes contributed by an item. This article also illustrates how to apply the item‐level ECA for attributes to estimate the correct classification rate of attributes patterns at the test level. Simulation results showed that two test‐level ECA indices, ECA_I_W (an index based on the independence assumption and the weighted sum of the item‐level ECAs) and ECA_C_M (an index based on Gaussian Copula function that incorporates the dependence structure of the events of attribute classification and the simple average of the item‐level ECAs), could make an accurate prediction for correct classification rates of attribute patterns. 相似文献
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We report a multidimensional test that examines middle grades teachers’ understanding of fraction arithmetic, especially multiplication and division. The test is based on four attributes identified through an analysis of the extensive mathematics education research literature on teachers’ and students’ reasoning in this content area. We administered the test to a national sample of 990 in‐service middle grades teachers and analyzed the item responses using the log‐linear cognitive diagnosis model. We report the diagnostic quality of the test at the item level, mastery classifications for teachers, and attribute relationships. Our results demonstrate that, when a test is grounded in research on cognition and is designed to be multidimensional from the onset, it is possible to use diagnostic classification models to detect distinct patterns of attribute mastery. 相似文献
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本研究旨在基于事先构建的理论模型,编制小学数学应用题认知诊断测验,并通过认知诊断评估对其效度进行验证。采用质性研究和量化研究两条思路,通过认知分析、大声思维和测验等方法,探索了认知诊断评估从理论模型构建到测验编制及其效度验证的过程。在理论模型构建和测验编制方面,所得结果表明认知分析和大声思维相结合能够合理地构建实质心理学的认知模型,并且基于该认知模型自上而下的测验设计是与认知诊断评估流程相吻合的。通过认知诊断评估所获取的数据分析表明,该测验的结构效度、内部效度和外部效度均达到理想水平,基于事先构建的认知模型所编制的认知诊断测验能够作为认知诊断评估的有效工具,有助于发掘和诊断学生数学应用题解决中的认知错误。 相似文献
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In cognitive diagnostic models (CDMs), a set of fine-grained attributes is required to characterize complex problem solving and provide detailed diagnostic information about an examinee. However, it is challenging to ensure reliable estimation and control computational complexity when The test aims to identify the examinee's attribute profile in a large-scale map of attributes. To address this problem, this study proposes a cognitive diagnostic multistage testing by partitioning hierarchically structured attributes (CD-MST-PH) as a multistage testing for CDM. In CD-MST-PH, multiple testlets can be constructed based on separate attribute groups before testing occurs, which retains the advantages of multistage testing over fully adaptive testing or the on-the-fly approach. Moreover, testlets are offered sequentially and adaptively, thus improving test accuracy and efficiency. An item information measure is proposed to compute the discrimination power of an item for each attribute, and a module assembly method is presented to construct modules anchored at each separate attribute group. Several module selection indices for CD-MST-PH are also proposed by modifying the item selection indices used in cognitive diagnostic computerized adaptive testing. The results of simulation study show that CD-MST-PH can improve test accuracy and efficiency relative to the conventional test without adaptive stages. 相似文献
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The attribute hierarchy method (AHM) is a psychometric procedure for classifying examinees' test item responses into a set of structured attribute patterns associated with different components from a cognitive model of task performance. Results from an AHM analysis yield information on examinees' cognitive strengths and weaknesses. Hence, the AHM can be used for cognitive diagnostic assessment. The purpose of this study is to introduce and evaluate a new concept for assessing attribute reliability using the ratio of true score variance to observed score variance on items that probe specific cognitive attributes. This reliability procedure is evaluated and illustrated using both simulated data and student response data from a sample of algebra items taken from the March 2005 administration of the SAT. The reliability of diagnostic scores and the implications for practice are also discussed. 相似文献
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Olga Kunina‐Habenicht André A. Rupp Oliver Wilhelm 《Journal of Educational Measurement》2012,49(1):59-81
Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item‐fit statistics for correct and misspecified diagnostic classification models within a log‐linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3 vs. 5), and items (25 vs. 50) as well as different attribute correlations (.50 vs. .80) and marginal attribute difficulties (equal vs. different). We investigated misspecifications of interaction effect parameters under correct Q‐matrix specification and two types of Q‐matrix misspecification. While the misspecification of interaction effects had little impact on classification accuracy, invalid Q‐matrix specifications led to notably decreased classification accuracy. Two proposed item‐fit indexes were more strongly sensitive to overspecification of Q‐matrix entries for items than to underspecification. Information‐based fit indexes AIC and BIC were sensitive to both over‐ and underspecification. 相似文献
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Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM‐based data with a linear attribute structure. The study utilizes a procedure to make the IRM and CDM frameworks comparable and investigates how estimation accuracy is affected by test diagnosticity and the match between the true and fitted models. The study shows that comparable results can be obtained when highly diagnostic IRM data are retrofitted with CDM, and vice versa, retrofitting CDMs to IRM‐based data in some conditions can result in considerable examinee misclassification, and model fit indices provide limited indication of the accuracy of item parameter estimation and attribute classification. 相似文献
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Hung‐Yu Huang 《Journal of Educational Measurement》2017,54(4):440-480
Cognitive diagnosis models (CDMs) have been developed to evaluate the mastery status of individuals with respect to a set of defined attributes or skills that are measured through testing. When individuals are repeatedly administered a cognitive diagnosis test, a new class of multilevel CDMs is required to assess the changes in their attributes and simultaneously estimate the model parameters from the different measurements. In this study, the most general CDM of the generalized deterministic input, noisy “and” gate (G‐DINA) model was extended to a multilevel higher order CDM by embedding a multilevel structure into higher order latent traits. A series of simulations based on diverse factors was conducted to assess the quality of the parameter estimation. The results demonstrate that the model parameters can be recovered fairly well and attribute mastery can be precisely estimated if the sample size is large and the test is sufficiently long. The range of the location parameters had opposing effects on the recovery of the item and person parameters. Ignoring the multilevel structure in the data by fitting a single‐level G‐DINA model decreased the attribute classification accuracy and the precision of latent trait estimation. The number of measurement occasions had a substantial impact on latent trait estimation. Satisfactory model and person parameter recoveries could be achieved even when assumptions of the measurement invariance of the model parameters over time were violated. A longitudinal basic ability assessment is outlined to demonstrate the application of the new models. 相似文献