De la prise en charge de la progression de l'interlocuteur vers un but à l'autorégulation des entreprises cognitives

Lorsque la visée de la communication est de comprendre et de se faire comprendre, les processus d'échange d'information requièrent le monitorage, tant intra qu'interpersonnel, de la progression vers le but à chaque étape de l'entreprise socio-cognitive. J. H. Flavell a puissamment contribué à éclairer les composantes cognitives de ce monitorage. Après avoir rappelé les principaux éléments de sa contribution, pertinents pour l'analyse des processus de communication, nous introduisons la dimension constituée par l'interaction interpersonnelle dans le monitorage. Nous essayons d'apporter des éléments montrant que c'est au coeur des échanges que s'effectue sa prise en charge cognitive. Nous poursuivons l'examen de la collaboration entre interlocuteurs en vue d'assurer la transmission de l'information au sein des structures de l'échange en pointant en particulier le monitorage et les régulations interpersonnelles. Enfin, nous situons notre point de vue parmi les théories ayant cherché à définir le rôle éventuellement structurant des interactions sociales dans l'acquisition d'expertise. Selon nous, les habiletés s'installent d'abord largement grâce à la communication de type asymétrique, une variété de processus étant en jeu alternativement, puis elles sont intériorisées—appropriées alors par le sujet qui devient capable de monitorer sa propre activité d'après les modèles observés d'abord chez autrui.     

Crisis Intervention With Survivors of Natural Disaster: Lessons From Hurricane Andrew

Crisis intervention has typically been conceptualized as seeking a return of clients to a state of equilibrium. Our work with Hurricane Andrew survivors in south Florida, as part of the Disaster Mental Health Services team of the American Red Cross, has led us to appreciate the importance of several further considerations. In our work, we developed a proactive approach, attempting to recognize and extend clients' preexisting strengths. We offer a number of pragmatic interventions, focusing particularly on children's issues and we draw attention to sensitive multicultural issues.     

A Playroom Observation Procedure to Assess Children with Mental Retardation and ADHD

Forty-two children (ages 6 to 12 years old) with moderate mental retardation to borderline intellectual functioning were studied in a laboratory playroom setting to determine whether children identified as ADHD (attention deficit hyperactivity disorder) or controls differed on activity and attentional measures. Children with ADHD were further divided into ADHD + conduct problems (ADHD + CD) and ADHD-only subgroups (with an ADHD-combined group comprising children of both subgroups). An interval recording system was used to code observations of independent play and a restricted academic task. Results indicated that the ADHD-combined group was significantly more vocal and engaged in a significantly greater number of toy changes than controls during independent play. Significant group differences were also noted during the restricted academic task, with the ADHD-combined and ADHD + CD groups more off-task and engaging in a greater number of toy touches than controls. Discriminant analyses found independent play measures to predict group membership in 70 percent of cases (ADHD-combined vs. controls), but in only 64 percent of cases using measures from the restricted academic task. No significant findings resulted when the ADHD subjects were further divided into two subgroups. Despite some inconsistent findings, such laboratory-based observations may be of value in the diagnosis of ADHD in children with moderate mental retardation to borderline intellectual functioning.     

Indclus: An individual differences generalization of the adclus model and the mapclus algorithm

We present a new model and associated algorithm, INDCLUS, that generalizes the Shepard-Arabie ADCLUS (ADditive CLUStering) model and the MAPCLUS algorithm, so as to represent in a clustering solution individual differences among subjects or other sources of data. Like MAPCLUS, the INDCLUS generalization utilizes an alternating least squares method combined with a mathematical programming optimization procedure based on a penalty function approach to impose discrete (0,1) constraints on parameters defining cluster membership. All subjects in an INDCLUS analysis are assumed to have a common set of clusters, which are differentially weighted by subjects in order to portray individual differences. As such, INDCLUS provides a (discrete) clustering counterpart to the Carroll-Chang INDSCAL model for (continuous) spatial representations. Finally, we consider possible generalizations of the INDCLUS model and algorithm.We are indebted to Seymour Rosenberg for making available the data from Rosenberg and Kim [1975]. Also, this work has benefited from the observations of S. A. Boorman, W. S. DeSarbo, G. Furnas, P. E. Green, L. J. Hubert, L. E. Jones, J. B. Kruskal, S. Pruzansky, D. Schmittlein, E. J. Shoben, S. D. Soli, and anonymous referees.This research was supported in part by NSF Grant SES82 00441, LEAA Grant 78-NI-AX-0142, and NSF Grant SES80 04815.     

Still no demonstration that g is not unitary: Further comment on Kranzler and Jensen

Because they employed a statistical procedure that was inappropriate for the purpose, Kranzler and Jensen (1991) have not demonstrated that a factor of general intelligence, g, depends on a number of independent processes. It is more parsimonious to interpret their results in terms of a g that is unitary. A factorial reanalysis of their data, including some that they did not present (cross-correlations between psychometric variables and variables from elementary cognitive tasks, or ECTs), shows that many ECT variables, especially those reflecting decision time rather than movement time, have substantial loadings on a second-order general factor. This factor is orthogonal to a second-order factor representing general speed of movement from a “home button” to the response button in ECTs. Possible implications for interpreting g in terms of information-processing efficiency are discussed.