Multiprofessional collaboration in teaching practices in all-day-schools in Switzerland

Multiprofessional collaboration in settings of extended education has been an important research topic in the past 40 years and has been discussed as a means to improve educational achievement, foster professional development, and support teachers in their everyday work. Several recent studies in multiprofessional settings found that collaboration practices often remain on a student-centered, time-limited, and superficial level of exchange, whereas higher forms of collaboration are very rare (Dizinger, Fussangel, Kasper, 2011). Furthermore there exists an obvious research gap on collaboration in Swiss all-day schools (Jutzi&Thomann, 2012). In this study we analyzed practices of multiprofessional collaboration in school-based and community-based extracurricular activities of all-day schools in Switzerland. The aim of this qualitative study of 10 all-day schools was to answer the following questions: (a) What forms of collaboration (informal/formal) are used between the different professionals? and (b) Are there different types of all-day schools with regard to distinctive and consistent types of collaboration? We conducted 18 problem-centered interviews (with the principals/heads of the all-day schools) and 10 focus group discussions (teams). In the process of data evaluation, we applied the method of qualitative content analysis. The results show that multiprofessional collabo ration is taking place in all of the all-day schools examined in the study. However, the collaborative practices differ in their level of intensity, design, and purpose.

First steps towards probabilistic justification logic

In this article, we introduce the probabilistic justification logic PJ, a logic in which we can reason about the probability of justification statements. We present its syntax and semantics, and establish a strong completeness theorem. Moreover, we investigate the relationship between PJ and the logic of uncertain justifications.

The Complexity of Non-Iterated Probabilistic Justification Logic

The logic PJ is a probabilistic logic defined by adding (noniterated) probability operators to the basic justification logic J. In this paper we establish upper and lower bounds for the complexity of the derivability problem in the logic PJ. The main result of the paper is that the complexity of the derivability problem in PJ remains the same as the complexity of the derivability problem in the underlying logic J, which is π[p/2] -complete. This implies that the probability operators do not increase the complexity of the logic, although they arguably enrich the expressiveness of the language.

Probabilistic Justification Logic

We present a probabilistic justification logic, PPJ, to study rational belief, degrees of belief and justifications. We establish soundness and completeness for PPJ and show that its satisfiability problem is decidable. In the last part we use PPJ to provide a solution to the lottery paradox.