Models postulating 2 distinct processing modes have been proposed in several topic areas within social and cognitive psychology. We advance a new conceptual model of the 2 processing modes. The structural basis of the new model is the idea, supported by psychological and neuropsychological evidence, that humans possess 2 memory systems. One system slowly learns general regularities, whereas the other can quickly form representations of unique or novel events. Associative retrieval or pattern completion in the slow-learning system elicited by a salient cue constitutes the effortless processing mode. The second processing mode is more conscious and effortful; it involves the intentional retrieval of explicit, symbolically represented rulesfrom either memory system and their use to guide processing. After presenting our model, we review existing dual-process models in several areas, emphasizing their similar assumptions of a quick, effortless processing mode that rests on well-learned prior associations and a second, more effortful processing mode that involves rule-based inferences and is employed only when people have both cognitive capacity and motivation. New insights and implications of the model for several topic areas are outlined.

Validating frameworks for understanding classroom processes that contribute to student learning and development is important to advance the scientific study of teaching. This article presents one such framework, Teaching through Interactions, which posits that teacher-student interactions are a central driver for student learning and organizes teacher-student interactions into three major domains. Results provide evidence that across 4,341 preschool to elementary classrooms (1) teacher-student classroom interactions comprise distinct emotional, organizational, and instructional domains; (2) the three-domain latent structure is a better fit to observational data than alternative one- and two-domain models of teacher-student classroom interactions; and (3) the three-domain structure is the best-fitting model across multiple data sets.

The present meta-analysis integrated effect sizes from 95 non-overlapping studies (N=15,826) to summarize the relation between Hare Psychopathy Checklists and antisocial conduct. Whereas prior meta-analyses focused on specific subdomains of the literature, we used broad inclusion criteria, incorporating a diversity of samples, settings, methodologies, and outcomes in our analysis. Our broad perspective allowed us to identify general trends consistent across the entire literature and improved the power of our analyses. Results indicated that higher PCL Total, Factor 1 (F(1)), and Factor 2 (F(2)) scores were moderately associated with increased antisocial conduct. Study effect sizes were significantly moderated by the country in which the study was conducted, racial composition, gender composition, institutional setting, the type of information used to score psychopathy, and the independence of psychopathy and transgression assessments. However, multiple regression analyses indicated that the information used to assess psychopathy did not have a unique influence on effect sizes after accounting for the influence of other moderator variables. Furthermore, racial composition of the sample was related to the country in which the study was conducted, making it unclear whether one or both of these moderators influenced effect sizes. We provide potential explanations for the significant findings and discuss implications of the results for future research.

Despite many articles reporting the problems of dichotomizing continuous measures, researchers still commonly use this practice. The authors' purpose in this article was to understand the reasons that people still dichotomize and to determine whether any of these reasons are valid. They contacted 66 researchers who had published articles using dichotomized variables and obtained their justifications for dichotomization. They also contacted 53 authors of articles published in Psychological Methods and asked them to identify any situations in which they believed dichotomized indicators could perform better. Justifications provided by these two groups fell into three broad categories, which the authors explored both logically and with Monte Carlo simulations. Continuous indicators were superior in the majority of circumstances and never performed substantially worse than the dichotomized indicators, but the simulations did reveal specific situations in which dichotomized indicators performed as well as or better than the original continuous indictors. The authors also considered several justifications for dichotomization that did not lend themselves to simulation, but in each case they found compelling arguments to address these situations using techniques other than dichotomization.