免费教育师范生学习适应状况及与报考动机的关系

该研究采用《大学生学习适应量表》考察了679名免费教育师范生的学习适应状况与特点,并探讨了报考动机与学习适应之间的关系。结果表明：1）免费教育师范生学习适应处于中等偏上水平,随着入学时间的增加逐步提高,且略优于普通大学生;2）免费教育师范生在学习适应的不同适应维度上存在性别差异;3）免费师范生报考动机有两大类：自愿报考和非自愿报考,报考动机对免费教育师范生学习适应水平具有显著的预测作用。免费教育师范生的学习适应总体上表现良好,报考动机直接影响入学后的学习适应水平。     

Can low Behavioral Activation System predict depressive mood?: An application of non‐normal structural equation modeling

Previous studies have reported a negative correlation between the Behavioral Activation System (BAS) and the depressive mood. However, which is the cause and which is the effect cannot be determined simply by evaluating the correlation coefficients. In a series of this study, we used non‐normal structural equation modeling, which could provide a statistically plausible answer to the question on the path direction. We tested for the path direction between the variables of interest by statistically comparing all possible models. The models assuming a unidirectional path from the BAS to the depressive mood were consistently supported. This suggested that low BAS could be a predisposition to developing the depressive mood. These findings could enhance our understanding of the mechanism underlying the development of the depressive mood.     

A similarity-based smoothing approach to nondimensional item analysis

The probability that an examinee chooses a particular option within an item is estimated by averaging over the responses to that item of examinees with similar response patterns for the whole test. The approach does not presume any latent variable structure or any dimensionality. But simulated and actual data analyses are presented to show that when the responses are determined by a latent ability variable, this similarity-based smoothing procedure can reveal the dimensionality of ability very satisfactorily.The author wishes to acknowledge the support of the Natural Sciences and Engineering Research Council of Canada through grant A320, and to thank Educational Testing Service for making the data on the Advanced Placement Chemistry Exam available.     

Fitting multivariage normal finite mixtures subject to structural equation modeling

This paper is about fitting multivariate normal mixture distributions subject to structural equation modeling. The general model comprises common factor and structural regression models. The introduction of covariance and mean structure models reduces the number of parameters to be estimated in fitting the mixture and enables one to investigate a variety of substantive hypotheses concerning the differences between the components in the mixture. Within the general model, individual parameters can be subjected to equality, nonlinear and simple bounds constraints. Confidence intervals are based on the inverse of the Hessian and on the likelihood profile. Several illustrations are given and results of a simulation study concerning the confidence intervals are reported.     

Estimation of interhemispheric dynamics from simple unimanual reaction time to extrafoveal stimuli

This essay reviews research on interhemispheric transfer time derived from simple unimanual reaction time to hemitachistoscopically presented visual stimuli. Part 1 reviews major theoretical themes including (a) the significance of the eccentricity effect on interhemispheric transfer time in the context of proposed underlying neurohistological constraints; (b) the significance of gender differences in interhemispheric transfer time and findings in dyslexics and left-handers in the context of a fetal brain testosterone model; and (c) the significance of complexity effects on interhemispheric transfer time in a context of dynamic vs. hard-wired concepts of the underlying interhemispheric communication systems. Part 2 consists of a meta-analysis of 49 published behavioral experiments, in view of drawing a portrait of the best set of experimental conditions apt to produce salient, reliable, and statistically significant measures of interhemispheric transfer time, namely (a) index rather than thumb response, (b) low rather than high target luminance, (c) short rather than prolonged target display, and (d) very eccentric rather than near-foveal stimulus location. Part 3 proposes a theoretical model of interhemispheric transfer time, postulating the measurable existence of fast and slow interhemispheric channels. The proposed mechanism's evolutionary adaptive value, the neurophysiological evidence in its support, and favorable functional evidence from studies of callosotomized patients are then presented followed by proposals for critical experimental tests of the model.     

贵州省高师本科大学生学业自我效能感与心理健康水平的研究

运用大学生学业自我效能感量表和SCL-90症状自评量表对高师本科大学生进行调查,探讨其学业自我效能感与心理健康水平的关系。结果表明：1、在学习能力自我效能感上,大一至大四学生无年级、性别、专业的显著差异;在学习行为自我效能感上,大三、大四差异显著;2、大四与其他各年级学生在自评症状各因子上存在极显著差异,男女生在自评症状的强迫和偏执两因子上存在显著差异;3、学业自我效能感高的学生与学业自我效能感低的学生在人际关系敏感、抑郁因子上差异显著;4、自我效能感与心理健康水平存在较高相关。     

师范生职业认同感的效能—价值双维核心模型的构建

以师范生职业认同感研究的"职业能力"和"职业价值"两大取向为基础,根据其单维评估的不足,将职业效能感和职业价值感指标联合,提出师范生职业认同感的效能—价值双维核心模型,并考察该模型在3所部属师范大学的1237名免费师范生中是否存在及其效用。研究表明:(1)模型能有效将免费师范生分组,其中低效能—低价值占31.69%、低效能—高价值占6.63%、高效能—低价值占40.01%、高效能—高价值仅占21.67%,克服了单维评估存在的高估或低估问题;(2)模型在职业认同结果(职业意志感、职业意愿与期望感)、学业满意度、总体生活满意度及未来担忧上的分组效应显著,同时拥有高职业效能感和高职业价值感的免费师范生具有最佳的职业认同感、学业满意度、总体生活满意度和最少的未来担忧。     

心理负荷对元记忆监测准确性及偏差的影响

以汉字再认任务为载体, 采用两因素被试内设计, 考察任务所导致的心理负荷水平, 以及学习判断(JOL)和信心判断(JOC)两种监测方式, 对元记忆监测效果的影响。对监测效果的衡量分别使用了相对准确性, 绝对准确性, 以及判断偏差三种指标。结果发现, 个体在任务过程中的心理负荷水平会影响其对任务解决过程的监测准确性:心理负荷水平越高, 元记忆监测的准确性越低。心理负荷水平还会影响元记忆监测的判断偏差:心理负荷处于中等偏低水平时, 监测不容易出现偏差;心理负荷处于中等偏高水平时, 个体表现出过高自信;但当心理负荷达到较高水平后, 判断偏差消失;随着心理负荷水平继续增大, 个体又表现出过低自信。     

Limits on Log Odds Ratios for Unidimensional Item Response Theory Models

Bounds are established for log odds ratios (log cross-product ratios) involving pairs of items for item response models. First, expressions for bounds on log odds ratios are provided for one-dimensional item response models in general. Then, explicit bounds are obtained for the Rasch model and the two-parameter logistic (2PL) model. Results are also illustrated through an example from a study of model-checking procedures. The bounds obtained can provide an elementary basis for assessment of goodness of fit of these models. Any opinions expressed in this publication are those of the authors and not necessarily those of the Educational Testing Service. The authors thank Dan Eignor, Matthias von Davier, Lydia Gladkova, Brian Junker, and the three anonymous reviewers for their invaluable advice. The authors gratefully acknowledge the help of Kim Fryer with proofreading.     

Bayesian estimation of a multilevel IRT model using gibbs sampling

In this article, a two-level regression model is imposed on the ability parameters in an item response theory (IRT) model. The advantage of using latent rather than observed scores as dependent variables of a multilevel model is that it offers the possibility of separating the influence of item difficulty and ability level and modeling response variation and measurement error. Another advantage is that, contrary to observed scores, latent scores are test-independent, which offers the possibility of using results from different tests in one analysis where the parameters of the IRT model and the multilevel model can be concurrently estimated. The two-parameter normal ogive model is used for the IRT measurement model. It will be shown that the parameters of the two-parameter normal ogive model and the multilevel model can be estimated in a Bayesian framework using Gibbs sampling. Examples using simulated and real data are given.