Informal interactions are often undervalued, yet, studies in office and educational environments show that they play an important role in successful collaborative projects. Online courses however, offer limited opportunities for informal interactions, which might put them at a disadvantage when compared to traditional courses. To evaluate possible technological solutions to this problem, we conducted a study of a computational system, designed to support informal interactions named CENTERS. The participants were 43 students from two different Mexican universities in four online courses, three undergraduate and one graduate. The data consisted of responses from two questionnaires, one applied at the beginning of the course and one at the end, and transcripts from all the courses. We tried to determine if the system increased the interaction among course participants, their satisfaction with the course, and if it helped reduce their feelings of isolation. Using multivariate statistical methods, including principal component analysis to detect possible associations among the variables, cluster analysis to measure the distances of similarity among the groups detected in the PCA and factor analysis to view the groupings of the parameters in their spatial arrangement, responses from our questionnaires were analyzed for associations among the variables considered in the study. Results suggest that CENTERS helps students reduce their feeling of isolation and increases collaboration among course participants. Additionally students who interacted more reported greater satisfied with the course in general, although this was not necessarily due to the use of the system.