Do testing effects change over time? Insights from immediate and delayed retrieval speed

Retrieving information from memory improves recall accuracy more than continued studying, but this testing effect often only becomes visible over time. In contrast, the present study documents testing effects on recall speed both immediately after practice and after a delay. A total of 40 participants learned the translation of 100 Swahili words and then further restudied the words with translations or retrieved the translations from memory during testing. As in previous experiments, recall accuracy was higher for restudied words than for tested words immediately after practice, but higher for tested words after 7 days. Response times for correct answers, however, showed a different result: Learners were faster to recall tested words than restudied words both immediately after practice and after 7 days. These results are interpreted in light of recent suggestions that testing selectively strengthens cue–response associations. An additional outcome was that testing effects on recall accuracy were related to perceived retrieval success during practice. When several practice retrievals were successful, testing effects on recall accuracy were already significant immediately after practice. Together with the reaction time data, this supports recent models that attribute changes in testing effects over time to limited item retrievability during practice.     

Examining Transfer Effects of Dual-Task Training Protocols for a Complex Locomotor Task

Training protocols designed to improve dual-task performance of an obstacle crossing and auditory Stroop task (OBS+Stroop) were tested. In Experiment 1, following baseline collection of OBS+Stroop trials, proximally related walking training was performed, and participants were then retested on the OBS+Stroop test. After training, participants adopted a more cautious obstacle crossing strategy, indicating a potentially safer navigation strategy. Transfer effects from distally related training were then examined (Experiment 2); a computer game training paradigm was examined using the same testing protocol as Experiment 1. Computer training demonstrated improved dual-task performance on some measures, but did not induce a more cautious stepping strategy. Results indicate that dual-task training needs to be similar to targeted tasks to yield reliable, positive training outcomes.     

Stepwise variable selection in factor analysis

It is very important to choose appropriate variables to be analyzed in multivariate analysis when there are many observed variables such as those in a questionnaire. What is actually done in scale construction with factor analysis is nothing but variable selection.In this paper, we take several goodness-of-fit statistics as measures of variable selection and develop backward elimination and forward selection procedures in exploratory factor analysis. Once factor analysis is done for a certain numberp of observed variables (thep-variable model is labeled the current model), simple formulas for predicted fit measures such as chi-square, GFI, CFI, IFI and RMSEA, developed in the field of the structural equation modeling, are provided for all models obtained by adding an external variable (so that the number of variables isp + 1) and for those by deleting an internal variable (so that the number isp – 1), provided that the number of factors is held constant.A programSEFA (Stepwise variable selection in Exploratory Factor Analysis) is developed to actually obtain a list of the fit measures for all such models. The list is very useful in determining which variable should be dropped from the current model to improve the fit of the current model. It is also useful in finding a suitable variable that may be added to the current model. A model with more appropriate variables makes more stable inference in general.The criteria traditionally often used for variable selection is magnitude of communalities. This criteria gives a different choice of variables and does not improve fit of the model in most cases.The URL of the programSEFA is http://koko15.hus.osaka-u.ac.jp/~harada/factor/stepwise/.     

Multilevel and Latent Variable Modeling with Composite Links and Exploded Likelihoods

Composite links and exploded likelihoods are powerful yet simple tools for specifying a wide range of latent variable models. Applications considered include survival or duration models, models for rankings, small area estimation with census information, models for ordinal responses, item response models with guessing, randomized response models, unfolding models, latent class models with random effects, multilevel latent class models, models with log-normal latent variables, and zero-inflated Poisson models with random effects. Some of the ideas are illustrated by estimating an unfolding model for attitudes to female work participation. We wish to thank The Research Council of Norway for a grant supporting our collaboration.     

心理学实验的可重复性

严格意义的实验可重复性指的是实验控制条件不变的情况下其结果的可重复性,置信区间是表示这种可重复性的恰当方法,可重复性的提高可通过在实验设计和数据分析中将影响因变量的随机额外变量作为协变量引入来实现;另一种意义的可重复性指的是实验结果的可迁移性,它涉及当控制条件变化时因控制变量和自变量的交互作用而导致的实验结果的变化。在这两种意义下,心理学实验较低的可重复性都源于它的额外变量的庞杂。     

Combining speed and accuracy to assess error-free cognitive processes

Both the speed and accuracy of responding are important measures of performance. A well-known interpretive difficulty is that participants may differ in their strategy, trading speed for accuracy, with no change in underlying competence. Another difficulty arises when participants respond slowly and inaccurately (rather than quickly but inaccurately), e.g., due to a lapse of attention. We introduce an approach that combines response time and accuracy information and addresses both situations. The modeling framework assumes two latent competing processes. The first, the error-free process, always produces correct responses. The second, the guessing process, results in all observed errors and some of the correct responses (but does so via non-specific processes, e.g., guessing in compliance with instructions to respond on each trial). Inferential summaries of the speed of the error-free process provide a principled assessment of cognitive performance reducing the influences of both fast and slow guesses. Likelihood analysis is discussed for the basic model and extensions. The approach is applied to a data set on response times in a working memory test. The authors wish to thank Roger Ratcliff, Christopher Chabris, and three anonymous referees for their helpful comments, and Aureliu Lavric for providing the data analyzed in this paper.     

The developmental course of processing speed in children with and without learning disabilities

This study contrasted the development of processing speed in children with and without learning disabilities. We examined whether the same global mechanism presumed to be responsible for the normal developmental improvement in processing speed might also be associated with the processing speed deficiencies observed in children with learning impairments. One hundred and twenty-two children with learning disabilities in reading and/or math and 206 non-disabled community controls participated. There were no differences in relation of age to the development of processing speed for children with and without learning disabilities. We interpreted these results as suggesting that the underlying etiologies for the normal developmental change in processing speed and for the relative deficiencies in processing speed seen among children with learning disabilities were different.     

Constituents of response rates

Response rate and the proportion of time pigeons allocated to a key-pecking activity were measured on several basic types of reinforcement schedules. Reinforcement frequency was varied within each type of basic schedule, and the effects on two constituents of response rate were noted. Propensity, the proportion of time the birds spent on a platform in front of the key, showed very consistent effects as reinforcement frequency varied: in general, it decreased when reinforcement frequency markedly decreased and it increased when reinforcement frequency increased. Speed, key pecks per unit of time spent on the platform, showed inconsistent effects when reinforcement frequency varied. Consequently, response rate showed less consistent effects than did propensity. Cumulative response records demonstrated the existence of several different types of transitions or boundary states between the key-pecking activity and other activities. The types of transitions that occurred between activities depended on both the type of reinforcement schedule and the frequency of reinforcement. The propensity data support the position that general laws of behavior can be based on temporal measures of behavior. The speed data suggest that, if a complete assessment of the dynamic properties of behavior is to be achieved, measures of behavior must incorporate the structural variations in the operant unit.