调节性匹配理论述评

在决策、动机领域,Higgins（2000）提出了一种新的理论——调节性匹配理论。所谓调节性匹配（regulatoryfit）,指的是个体的自我调节定向与其行为策略之间的匹配。该理论认为,调节性匹配能增强个体在目标追求过程中的动机强度、主观评价和情绪体验,从而对个体的行为决策产生重要影响。文章围绕调节性匹配的概念、产生、效应及应用价值等问题对相关研究进行综述,并在此基础上提出了现有研究存在的问题及未来的研究方向     

具有认知诊断功能的计算机化自适应测验的研究与实现

构造具有认知诊断功能的计算机化自适应测验（Computerized Adaptive Testing,CAT）,关键在于设计不同于传统CAT的选题策略。本文采用先认知诊断后估计能力的方法,在诊断阶段用状态转换图描述特定认知领域中所有知识状态及这些状态之间的联系,以图的深度优先算法为基础设计选题策略;而在能力估计精细化阶段,每个被试所测项目,不仅与其能力估计值相匹配,且只与其所掌握的属性相关。本文采用蒙特卡罗模拟针对三种不同的属性结构进行试验,结果良好     

个人-工作契合度测量研究的新进展

论文概述了个人-工作契合度测量研究的发展，介绍了测量的角度、测量的内容、方法和指标，分析比较了各种方法的优缺点，最后总结了现有的测量研究的局限并对未来研究的发展趋势作了展望。     

An accumulator model for responses and response times in tests based on the proportional hazards model

Latent trait models for responses and response times in tests often lack a substantial interpretation in terms of a cognitive process model. This is a drawback because process models are helpful in clarifying the meaning of the latent traits. In the present paper, a new model for responses and response times in tests is presented. The model is based on the proportional hazards model for competing risks. Two processes are assumed, one reflecting the increase in knowledge and the second the tendency to discontinue. The processes can be characterized by two proportional hazards models whose baseline hazard functions correspond to the temporary increase in knowledge and discouragement. The model can be calibrated with marginal maximum likelihood estimation and an application of the ECM algorithm. Two tests of model fit are proposed. The amenability of the proposed approaches to model calibration and model evaluation is demonstrated in a simulation study. Finally, the model is used for the analysis of two empirical data sets.     

Comparing score tests and other local dependence diagnostics for the graded response model

Score tests for identifying locally dependent item pairs have been proposed for binary item response models. In this article, both the bifactor and the threshold shift score tests are generalized to the graded response model. For the bifactor test, the generalization is straightforward; it adds one secondary dimension associated only with one pair of items. For the threshold shift test, however, multiple generalizations are possible: in particular, conditional, uniform, and linear shift tests are discussed in this article. Simulation studies show that all of the score tests have accurate Type I error rates given large enough samples, although their small‐sample behaviour is not as good as that of Pearson's Χ² and M₂ as proposed in other studies for the purpose of local dependence (LD) detection. All score tests have the highest power to detect the LD which is consistent with their parametric form, and in this case they are uniformly more powerful than Χ² and M₂; even wrongly specified score tests are more powerful than Χ² and M₂ in most conditions. An example using empirical data is provided for illustration.     

Does work engagement increase person–job fit? The role of job crafting and job insecurity

Drawing on the expanded model of person–environment fit and job crafting theory, this study investigates the underlying processes of the relationship between work engagement and changes in person–job fit. A two-wave longitudinal study was conducted among 246 Chinese employees of a high technology company. As hypothesized, the results show that work engagement is positively related to changes in demands–abilities fit through changes in physical job crafting and positively related to changes in needs–supplies fit through changes in relational job crafting. As predicted, the positive relationship between work engagement and changes in relational job crafting (however, not changes in physical job crafting) is strengthened under conditions of high (vs. low) job insecurity. Our findings indicate that engaged employees craft their work in physical and relational ways, which creates a better person–job fit. The theoretical and practical implications are discussed.     

The Effect of Propensity Scores on DIF Analysis: Inference on the Potential Cause of DIF

Differential item functioning (DIF) analysis is important in terms of test fairness. While DIF analyses have mainly been conducted with manifest grouping variables, such as gender or race/ethnicity, it has been recently claimed that not only the grouping variables but also contextual variables pertaining to examinees should be considered in DIF analyses. This study adopted propensity scores to incorporate the contextual variables into the gender DIF analysis. In this study, propensity scores were used to control for the contextual variables that potentially affect the gender DIF. Subsequent DIF analyses with the Mantel-Haenszel (MH) procedure and the Logistic Regression (LR) model were run with the propensity score applied reference (males) and focal groups (females) through propensity score matching. The propensity score embedded MH model and LR model detected fewer number of gender DIF than the conventional MH and LR models. The propensity score embedded models, as a confirmatory approach in DIF analysis, could contribute to hypothesizing an inference on the potential cause of DIF. Also, salient advantages of propensity score embedded DIF analysis models are discussed.     

Uncovering Substantive Patterns in Student Responses in International Large-Scale Assessments—Comparing a Latent Class to a Manifest DIF Approach

In this study, we contrast results from two differential item functioning (DIF) approaches (manifest and latent class) by the number of items and sources of items identified as DIF using data from an international reading assessment. The latter approach yielded three latent classes, presenting evidence of heterogeneity in examinee response patterns. It also yielded more DIF items with larger effect sizes and more consistent item response patterns by substantive aspects (e.g., reading comprehension processes and cognitive complexity of items). Based on our findings, we suggest empirically evaluating the homogeneity assumption in international assessments because international populations cannot be assumed to have homogeneous item response patterns. Otherwise, differences in response patterns within these populations may be under-detected when conducting manifest DIF analyses. Detecting differences in item responses across international examinee populations has implications on the generalizability and meaningfulness of DIF findings as they apply to heterogeneous examinee subgroups.     

题组反应理论及其在中学英语考试中的应用研究

题组作为众多测验中的一种常见题型,由于项目间存在一定程度的依赖性而违背了局部独立性假设,若用项目反应模型进行参数估计将会出现较大的偏差.题组反应理论将被试与题组的交互作用纳入到模型中,解决了项目间相依性的问题.笔者对题组反应理论的发展、基本原理及其相关研究进行了综述,并将其应用在中学英语考试中.与项目反应理论相对比,结果发现：（1）题组反应模型与项目反应模型在各参数估计值的相关系数较强,尤其是能力参数和难度参数;（2）在置信区间宽度的比较上,题组反应模型在各个参数上均窄于项目反应模型,即题组反应模型的估计精度优于项目反应模型.     

Engagement and Disengagement in Mutual-Help Addiction Recovery Housing: A Test of Affective Events Theory

This study tested an affective events theory (AET) model in the Oxford House network of recovery homes. Residents’ congruence with their home (P–E fit) was hypothesized to directly influence behavior that supported the house and other residents—citizenship behavior. We further hypothesized P–E fit would be related to member intentions to leave, with attitudes toward the home mediating that relationship. To assess this, we administered a cross‐sectional national survey to 296 residents of 83 randomly selected Oxford Houses. Although the AET model demonstrated good fit with the data, an alternative model fit better. This alternative model suggested an additional indirect relationship between P–E fit and citizenship mediated by attitudes. Results suggested affective experiences such as feeling like one fits with a community may influence engagement and disengagement. There appears to be a direct influence of fit on citizenship behavior and an indirect influence of fit through recovery home attitudes on both citizenship and intentions to leave the home. We conclude affective experiences could be important for community engagement and disengagement but AET may need to integrate cognitive dissonance theory.