Flexible analysis of user actions in heterogeneous distributed learning environments

In this paper, we describe an architectural framework for the engineering of distributed learning environments with different devices and multi-language agent support. The framework consists of a central Tuple Space server and clients that differ in hardware (PDAs, PCs with projection) and in programming languages (C#, Prolog, Java). The analysis components use state patterns and action patterns to be defined in and interpreted by Prolog. This framework has been used for supporting the design rationale method QOC in a collaborative visual modelling environment.