Learning spaces as representational scaffolds for learning conceptual knowledge of system behaviour

Scaffolding is a well-known approach to bridge the gap between novice and expert capabilities in a discovery-oriented learning environment. This paper discusses a set of knowledge representations referred to as Learning Spaces (LSs) that can be used to support learners in acquiring conceptual knowledge of system behaviour. The LSs are logically self-contained, meaning that models created at a specific LS can be simulated. Working with the LSs provides scaffolding for learners in two ways. First, each LS provides a restricted set of representational primitives to express knowledge, which focus the learner’s knowledge construction process. Second, the logical consequences of an expression derived upon simulating, provide learners a reflective instrument for evaluating the status of their understanding, to which they can react accordingly.
The work presented here is part of the DynaLearn project, which builds an Interactive Learning Environment to study a constructive approach to having learners develop a qualitative understanding of how systems behave. The work presented here thus focuses on tools to support educational research. Consequently, user-oriented evaluation of these tools is not a part of this paper.