Longitudinal Predictive Validity of a Learning Potential Test

The aim of this article is to provide empirical psychometric evidence of the (longitudinal) predictive validity of a learning potential measure—the Learning Potential Computerised Adaptive Test (LPCAT)—in comparison with standard static tests with school aggregate results as the criterion measure. Participants were 79 boys (mean age 12.44, SD = 0.44) and 72 girls (mean age 11.18, SD = 0.42) attending two private schools. Correlation and regression analyses were used to evaluate the predictive validity of the learning potential and standard test scores for school aggregate academic results as criterion measure. Results indicate that learning potential scores were statistically significant predictors of aggregate academic results and provided results that were comparable to those of the standard test results—providing empirical support for the use of learning potential tests in mainstream educational settings.     

On the asymptotic standard error of a class of robust estimators of ability in dichotomous item response models

In item response theory, the classical estimators of ability are highly sensitive to response disturbances and can return strongly biased estimates of the true underlying ability level. Robust methods were introduced to lessen the impact of such aberrant responses on the estimation process. The computation of asymptotic (i.e., large‐sample) standard errors (ASE) for these robust estimators, however, has not yet been fully considered. This paper focuses on a broad class of robust ability estimators, defined by an appropriate selection of the weight function and the residual measure, for which the ASE is derived from the theory of estimating equations. The maximum likelihood (ML) and the robust estimators, together with their estimated ASEs, are then compared in a simulation study by generating random guessing disturbances. It is concluded that both the estimators and their ASE perform similarly in the absence of random guessing, while the robust estimator and its estimated ASE are less biased and outperform their ML counterparts in the presence of random guessing with large impact on the item response process.     

Limited‐information goodness‐of‐fit testing of diagnostic classification item response models

Despite the growing popularity of diagnostic classification models (e.g., Rupp et al., 2010, Diagnostic measurement: theory, methods, and applications, Guilford Press, New York, NY) in educational and psychological measurement, methods for testing their absolute goodness of fit to real data remain relatively underdeveloped. For tests of reasonable length and for realistic sample size, full‐information test statistics such as Pearson's X² and the likelihood ratio statistic G² suffer from sparseness in the underlying contingency table from which they are computed. Recently, limited‐information fit statistics such as Maydeu‐Olivares and Joe's (2006, Psychometrika, 71, 713) M₂ have been found to be quite useful in testing the overall goodness of fit of item response theory models. In this study, we applied Maydeu‐Olivares and Joe's (2006, Psychometrika, 71, 713) M₂ statistic to diagnostic classification models. Through a series of simulation studies, we found that M₂ is well calibrated across a wide range of diagnostic model structures and was sensitive to certain misspecifications of the item model (e.g., fitting disjunctive models to data generated according to a conjunctive model), errors in the Q‐matrix (adding or omitting paths, omitting a latent variable), and violations of local item independence due to unmodelled testlet effects. On the other hand, M₂ was largely insensitive to misspecifications in the distribution of higher‐order latent dimensions and to the specification of an extraneous attribute. To complement the analyses of the overall model goodness of fit using M₂, we investigated the utility of the Chen and Thissen (1997, J. Educ. Behav. Stat., 22, 265) local dependence statistic $X_{\mathrm{LD}}^2$ for characterizing sources of misfit, an important aspect of model appraisal often overlooked in favour of overall statements. The $X_{\mathrm{LD}}^2$ statistic was found to be slightly conservative (with Type I error rates consistently below the nominal level) but still useful in pinpointing the sources of misfit. Patterns of local dependence arising due to specific model misspecifications are illustrated. Finally, we used the M₂ and $X_{\mathrm{LD}}^2$ statistics to evaluate a diagnostic model fit to data from the Trends in Mathematics and Science Study, drawing upon analyses previously conducted by Lee et al., (2011, IJT, 11, 144).     

Concurrent cognitive processes in rat serial pattern learning: II. Discrimination learning,rule learning,chunk length,and multiple‐item memories

The current experiment examined the factors that determine acquisition for elements of highly structured serial patterns. Three groups of rats were trained on three patterns with parallel rule‐based hierarchical structure, but with 3‐, 4‐, or 5‐element chunks, each with a final violation element. Once rats mastered their patterns, probe patterns were introduced to answer several questions. To assess the extent to which the learned response pattern depended on intrachamber location cues for anticipating different element types, Spatial Shift Probes shifted the starting lever of patterns to locations that positioned chunk boundaries where they had never been experienced during training. To assess the extent to which a phrasing cue is necessary for rats to perform a chunk‐boundary response, a Cue Removal Probe tested whether rats would produce a chunk‐boundary response in the correct serial position if the phrasing cue was omitted. To assess the extent to which cues from multiple trials leading up to the violation element are required to anticipate the violation element, Multiple‐Item Memory Probes required rats to make an unexpected response on one of the elements in the last two chunks of the pattern prior to the violation element. The results indicated that rats used multiple concurrent learning and memory processes to master serial patterns, including discrimination learning, rule learning, encoding of chunk length, and multiple‐item memories.     

Consistent Differential Discrimination Model Estimation

A novel factor-analytic model—the differential discrimination model—for assessing individual differences in scale use has been recently introduced, together with a three-stage estimation approach for model fitting. Unfortunately, the second-stage estimator and, as a consequence, the third-stage estimator of this procedure are not consistent. In this article we show that (a) the differential discrimination model can be expressed in a structural equation model framework, and (b) consistent and simultaneous estimation of all model parameters can be achieved using standard SEM software.     

考虑题目选项信息的非参数认知诊断计算机自适应测验

选择题中的作答选项能提供额外诊断信息, 为充分利用选项信息, 研究提出认知诊断计算机自适应测验(CD-CAT)中两种处理选择题选项信息的非参数选题策略和变长终止规则。模拟研究的结果发现：(1)定长条件下两种非参数选题策略的分类准确性整体要高于参数选题策略; (2)两种非参数选题策略较参数选题策略具有更加均衡的题库使用情况; (3)非参数选题策略在两种新的变长终止规则下具有更高的分类准确率; (4)两种非参数选题策略均适用于选择题CD-CAT情境, 使用者可任选其一进行测验分析。     

认知诊断框架下多级评分题目的DIF检测方法及其应用

本文对多级计分认知诊断测验的DIF概念进行了界定,并通过模拟实验以及实证研究对四种常见的多级计分DIF检验方法的适用性进行理论以及实践性的探索。研究结果表明：四种方法均能对多级计分认知诊断中的DIF进行有效的检验,且各方法的表现受模型的影响不大;相较于以总分为匹配变量,以KS为匹配变量时更利于DIF的检测;以KS为匹配变量的LDFA方法以及以KS为匹配变量的曼特尔检验方法在检测DIF题目时有着最高的检验力。     

两种范式下有意遗忘的实验研究

本文以英语词汇为材料,采用自由回忆和再认测验作为外显记忆测验,词干补笔测验作为内隐记忆测验,探讨小学五年级学生在单字范式与字表范式下的有意遗忘效应及其机制。结果发现:(1)单字范式下,三种测验中都存在有意遗忘效应;而字表范式下,只有词干补笔和自由回忆测验中存在有意遗忘效应;(2)三种测验中,单字范式下记忆项与遗忘项的差异显著高于字表范式下二者的差异。这表明,两种范式下有意遗忘效应产生的机制是不一致的,且相较于字表范式,单字范式下有意遗忘效应更显著。     

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。     

心理健康素质测评系统·中国成年人一般自我概念量表的编制

旨在编制适合中国成年人的一般自我概念测量工具。通过理论分析,建构了一般自我概念的四个维度,包括积极性、清晰性、悦纳性和调节性,并据此编制了中国成年人一般自我概念量表。分别选取北京地区450名和400名大学生进行预试和正式测试：验证性因素分析表明,建构的一般自我概念四维测量模型结构合理,拟合良好;项目及信效度分析表明,量表各项目区分度良好,信、效度符合心理测量学要求。因此,该量表可作为成年人一般自我概念和自我心理健康素质的测量工具。