Bilingual memory research in the past decade and, particularly, in the past five years, has developed a range of sophisticated experimental, neuropsychological and computational techniques that have allowed researchers to begin to answer some of the major long-standing questions of the field. We explore bilingual memory along the lines of the conceptual division of language knowledge and organization, on the one hand, and the mechanisms that operate on that knowledge and organization, on the other. Various interactive-activation and connectionist models of bilingual memory that attempt to incorporate both organizational and operational considerations will serve to bridge these two divisions. Much progress has been made in recent years in bilingual memory research, which also serves to illuminate general (language-independent) memory processes.

Dijkstra and van Heuven have made an admirable attempt to develop a new model of bilingual memory, the BIA+. Their article presents a clear and well-reasoned theoretical justification of their model, followed by a description of their model. The BIA+ is, as the name implies, an extension of the Bilingual Interactive Activation (BIA) model (Dijkstra and van Heuven, 1998; Van Heuven, Dijkstra and Grainger, 1998; etc), which was itself an adaptation to bilingual memory of McClelland and Rumelhart's (1981) Interactive Activation model of monolingual memory.

Although we are not necessarily in disagreement with the comment by Costa and Santesteban [1], neither are we as convinced as they are of the need for two modalities, one for word production, the other for word recognition. Their key claim is that 'in word production, it is the speaker who intentionally chooses the target language'. Perhaps at the moment of actually switching languages, one could argue for a need for a top-down intentional switching mechanism. But during most language production, simpler, automatic mechanisms of word activation -identical to those at work in word recognition -would suffice to keep the bilingual speaker in one or the other language. Each word in a particular language whether it is spoken or heard, activates a halo of other words -virtually all of which are in the same language -and, as a result, it requires no particular intentional effort for a bilingual to remain in that language. If you are having a financial discussion, it requires no intentional effort to remain in a financial context, as opposed to say, a culinary context. The same applies, we believe, for languages. It strikes us that the underlying mechanism of spreading activation suffices to explain (virtually) all of both word production as well as word recognition.Further, throughout our article we emphasize the importance of the role of the task. In a task requiring you to switch languages at the end of each sentence, there would, indeed, be a great deal of intentional effort involved in doing so and, in this case, Costa and Santesteban's point would certainly be correct. On the other hand, if you ask people to produce, as quickly as possible, the first word that comes to mind when they hear the utterance, 'What do cows drink?' they will produce 'milk', independently of any intentional desire to do so. This could reasonably be called non-intentional (bottom-up) word production.Our point is that, although we are certainly not opposed to different mechanisms or combinations of processes for word production and word recognition, the case for this has to be made empirically. It is not enough simply to state the necessity of intentionality in specific-language word production and then conclude that this implies the existence of separate word production and word recognition mechanisms (i.e. different combinations of processes occurring in word perception compared with word production). In short, all cases of word production are not created equal.

Dans le cadre de la lutte contre l'échec en premier cycle supérieur, le LabSET et des enseignants de physique de l'université de Liège ont développé un dispositif en ligne d'entraînement à la résolution de problèmes en physique. Deux problématiques sont abordées ici : le diagnostic de la maîtrise des processus cognitifs à mobiliser pour résoudre des problèmes de physique et le lien entre entraînement en ligne et performance des étudiants lors de la résolution de problèmes à l'examen. Les analyses reposent sur une étude menée auprès de 876 étudiants inscrits en première année en médecine. Elles ont été effectuées sur la base des données subjectives (auto-évaluation du processus et du produit) et objectives (nombre de connexions aux exercices en ligne, résultats de maîtrise des questions spécifiques aux processus cognitifs étudiés, taux de réussite et notes aux examens). Les résultats indiquent que le processus d'analyse est celui posant le plus de difficultés aux étudiants. De plus, une dépendance est observée entre travail en ligne et réussite aux problèmes présentés à l'examen de juin. Les notes des étudiants ayant travaillé en ligne sont supérieures à celles des étudiants n'ayant réalisé aucun problème en ligne. Cependant, étant donné que les étudiants ayant réussi l'examen de physique sont aussi ceux ayant réussi les épreuves dans les autres matières scientifiques, il est difficile d'établir un rapport de causalité entre travail en ligne et performances.: télé-apprentissage, résolution de problèmes, diagnostic, entraînement à une tâche, processus cognitif Online training platform for resolution of problems in physics As part of projects aiming to reduce failure during bachelor studies, LabSET and physics teachers of the university of Liège developed an online package designed to improve skills in solving physics problems. Research focuses, on one hand, on diagnosis as to whether cognitive processes used in solving physics problems are mastered by the user or not and, on the other hand, on the link between effective online training and students performance at solving examination problems. Analyses rely on a 1 study conducted with 876 first-year medicine students. They were performed on the basis of subjective (self-evaluation of process and product) and objective (number of connections, results on specific questions for each cognitive process, passing rate and examination results) data. At the end of the research, we observed that the analysis process is the one for which the students show most difficulties. Almost 50 % of the students are aware of this. Although the strength of association is weak to medium, dependence is observed between online work and success at solving the examination problems. The results of students who worked online are higher than those of students who did not. However, considering that students who passed the physics examination also passed the examinations on other scientific subjects, it is difficult to establish a causality link between online work and performance.