Item-Specificity and Intention in Episodic Memory.

Schmidt et al.'s (2020) PEP model accurately reflects the complexity of task switching based on bottom-up assumptions and episodic memory, re-evaluating the contribution of commonly presumed top-down processes. Extending it to long-term bindings and their item-specific effects could eludicate puzzling findings regarding the independence of long-term bindings between stimuli, responses, and task-specific categorizations as well as the relation between short-term and long-term bindings. Moreover, ideomotor theories of action control provide a bottom-up basis of incorporating volition and intentional action into the PEP model which is currently restricted to stimulus-based action.

An Application of Reliability Estimation in Longitudinal Designs Through Modeling Item-Specific Error Variance.

The purpose of the present study was to apply the methodology developed by Raykov on modeling item-specific variance for the measurement of internal consistency reliability with longitudinal data. Participants were a randomly selected sample of 500 individuals who took on a professional qualifications test in Saudi Arabia over four different occasions. Data were analyzed by use of confirmatory factor analysis, and item error variance was corrected for item specificity. The estimation of reliability involved composite index omega. Results indicated that the initially low and unacceptable levels of internal consistency reliability approached acceptable levels after accounting for item-specific variance. Findings were verified by testing whether the difference estimates of internal consistency reliability deviated from a zero-mean distribution using 10,000 replicated samples assuming a known (symmetric) or unknown (asymmetric) population distribution of the difference reliability coefficients. Percentage improvement reliability estimates indices were also estimated along with their 95% confidence intervals. Two appendices provide annotated Mplus syntax files for future use.

Category learning in the color-word contingency learning paradigm.

In the typical color-word contingency learning paradigm, participants respond to the print color of words where each word is presented most often in one color. Learning is indicated by faster and more accurate responses when a word is presented in its usual color, relative to another color. To eliminate the possibility that this effect is driven exclusively by the familiarity of item-specific word-color pairings, we examine whether contingency learning effects can be observed also when colors are related to categories of words rather than to individual words. To this end, the reported experiments used three categories of words (animals, verbs, and professions) that were each predictive of one color. Importantly, each individual word was presented only once, thus eliminating individual color-word contingencies. Nevertheless, for the first time, a category-based contingency effect was observed, with faster and more accurate responses when a category item was presented in the color in which most of the other items of that category were presented. This finding helps to constrain episodic learning models and sets the stage for new research on category-based contingency learning.