Piecewise method of reciprocal averages for dual scaling of multiple-choice data

The proposed method handles the classical method of reciprocal averages (MRA) in a piecewise (item-by-item) mode, whereby one can deal with smaller matrices and attain faster convergence to a solution than the MRA. A new concept the principle of constant proportionality is introduced to provide an interesting interpretation for scaling multiple-choice data a la Guttman. A small example is presented for discussion of the technique.This study was supported by the Natural Sciences and Engineering Research Council Canada Grant (No. A4581) to S. Nishisato. The authors are indebted to reviewers for valuable comments.     

A technique for the nonmetric analysis of paired comparisons of psychological intervals

A nonmetric coordinate adjustment technique is developed which determines scale values for objects whose interobject intervals (differences in subjective value) have been directly compared. In Monte Carlo simulations, the degree of metric determinancy of the scale values is shown to be quite high even when the amount of error is relatively high. This robustness under high-error conditions permitted the analysis of individual subject data in experiments on the direct comparison of loudness differences and loudness ratios where only one judgment per interval comparison was obtained per subject.This research was supported by a grant from the National Research Council of Canada.     

V.A. Smirnov’s Results in the Field of Modern Formal Logic

This paper is a survey of V.A. Smirnovs main results in modern logic.     

A Gibbs sampler for the multidimensional four-parameter logistic item response model via a data augmentation scheme

The four-parameter logistic (4PL) item response model, which includes an upper asymptote for the correct response probability, has drawn increasing interest due to its suitability for many practical scenarios. This paper proposes a new Gibbs sampling algorithm for estimation of the multidimensional 4PL model based on an efficient data augmentation scheme (DAGS). With the introduction of three continuous latent variables, the full conditional distributions are tractable, allowing easy implementation of a Gibbs sampler. Simulation studies are conducted to evaluate the proposed method and several popular alternatives. An empirical data set was analysed using the 4PL model to show its improved performance over the three-parameter and two-parameter logistic models. The proposed estimation scheme is easily accessible to practitioners through the open-source IRTlogit package.     

A Person Fit Test For Irt Models For Polytomous Items

A person fit test based on the Lagrange multiplier test is presented for three item response theory models for polytomous items: the generalized partial credit model, the sequential model, and the graded response model. The test can also be used in the framework of multidimensional ability parameters. It is shown that the Lagrange multiplier statistic can take both the effects of estimation of the item parameters and the estimation of the person parameters into account. The Lagrange multiplier statistic has an asymptotic χ²-distribution. The Type I error rate and power are investigated using simulation studies. Results show that test statistics that ignore the effects of estimation of the persons’ ability parameters have decreased Type I error rates and power. Incorporating a correction to account for the effects of the estimation of the persons’ ability parameters results in acceptable Type I error rates and power characteristics; incorporating a correction for the estimation of the item parameters has very little additional effect. It is investigated to what extent the three models give comparable results, both in the simulation studies and in an example using data from the NEO Personality Inventory-Revised.     

具有创造成就的科学家关于创造的概念结构

运用Q分类及多尺度分析方法,研究具有创造成就的科学家关于创造成就的概念结构。被试是30名来自物理、化学、数学、地学和生命科学领域的具有创造成就的科学家。研究发现,具有创造成就的科学家关于创造成就的概念结构由“成就取向/内心体验取向”、“主动进取/踏实肯干”两个维度构成;取得科学创造成就的重要特征是“成就取向”和“主动进取”。作者进一步讨论了主动进取对于取得创造性成就的意义     

First demonstration of effective spatial training for near transfer to spatial performance and far transfer to a range of mathematics skills at 8 years

There is evidence that spatial thinking is malleable, and that spatial and mathematical skills are associated (Mix et al. [2016] Journal of Experimental Psychology: General, 145, 1206; Mix et al. [2017] Journal of Cognition and Development, 18, 465; Uttal et al. [2013] Psychological Bulletin, 139, 352). However, few studies have investigated transfer of spatial training gains to mathematics outcomes in children, and no known studies have compared different modes of spatial instruction (explicit vs. implicit instruction). Based on a sample of 250 participants, this study compared the effectiveness of explicit and implicit spatial instruction in eliciting near transfer (to the specific spatial skills trained), intermediate transfer (to untrained spatial skills) and far transfer (to mathematics domains) at age 8. Spatial scaling and mental rotation skills were chosen as training targets as previous studies have found, and proposed explanations for, associations between these skills and mathematics in children of this age (Journal of Experimental Psychology: General, 145, 2016 and 1206). In this study, spatial training led to near, intermediate and far transfer of gains. Mental visualization and proportional reasoning were proposed to explain far transfer from mental rotation and spatial scaling skills respectively. For most outcomes, except for geometry, there was no difference in the effectiveness of implicit (practice with feedback) compared to explicit instruction (instructional videos). From a theoretical perspective, the study identified a specific causal effect of spatial skills on mathematics skills in children. Practically, the results also highlight the potential of instructional videos as a method of introducing spatial thinking into the classroom.     

基于多维题组反应模型的项目功能差异检验探究

本文将多维题组反应模型（MTRM）应用到多维题组测验的项目功能差异（DIF）检验中,通过模拟研究和应用研究探究MTRM在DIF检验中的准确性、有效性和影响因素,并与忽略题组效应的多维随机系数多项Logistic模型（MRCMLM）进行对比。结果表明：（1）随着样本量的增大,MTRM对有效DIF值检出率增高,错误率降低,在不同条件下结果的稳定性更高;（2）与MRCMLM相比,基于MTRM的DIF检验模型检验率更高,受到其他因素的影响更小;（3）当测验中题组效应较小时,MTRM与MRCMLM结果差异较小,但是MTRM模型拟合度更高。     

Measurement of Ability in Adaptive Learning and Assessment Systems when Learners Use On-Demand Hints

Adaptive learning and assessment systems support learners in acquiring knowledge and skills in a particular domain. The learners’ progress is monitored through them solving items matching their level and aiming at specific learning goals. Scaffolding and providing learners with hints are powerful tools in helping the learning process. One way of introducing hints is to make hint use the choice of the student. When the learner is certain of their response, they answer without hints, but if the learner is not certain or does not know how to approach the item they can request a hint. We develop measurement models for applications where such on-demand hints are available. Such models take into account that hint use may be informative of ability, but at the same time may be influenced by other individual characteristics. Two modeling strategies are considered: (1) The measurement model is based on a scoring rule for ability which includes both response accuracy and hint use. (2) The choice to use hints and response accuracy conditional on this choice are modeled jointly using Item Response Tree models. The properties of different models and their implications are discussed. An application to data from Duolingo, an adaptive language learning system, is presented. Here, the best model is the scoring-rule-based model with full credit for correct responses without hints, partial credit for correct responses with hints, and no credit for all incorrect responses. The second dimension in the model accounts for the individual differences in the tendency to use hints.     

Consensus scoring, correct responses and reliability of the MSCEIT V2

The scoring protocol adopted by the MSCEIT V2 has been criticised since its development. The present study raises questions regarding the value of consensus scoring by analysing responses within the categorical subscales of Changes and Blends using the Optimal Scaling technique within the Categorical Principal Components Analysis (CATPCA) via Statistical Package for the Social Sciences (SPSS), (n = 206). On a number of occasions, there was no clear agreement as to the “correct” response to items within these categorical subscales. Such an issue seems integral to the application of the MSCEIT V2 and one which deserves more attention. On a more positive note, improvements were made to the reliabilities of the subscales of Changes and Blends, using Optimal Scaling, but less so for Changes. Nevertheless, this raises the possibility of improving the reliabilities of other subscales in the MSCEIT V2 and in turn improving the power of subsequent statistical tests.