Graph of Microworlds: A Framework for Assisting Progressive Knowledge Acquisition in Simulation-based Learning Environments

A framework for assisting a learner’s progressive knowledge acquisition in simulation-based learning environments (SLEs) is proposed. In SLE, usually a learner is first given a simple situation to acquire basic knowledge, then given more complicated situation to refine it. Such change of situation often causes the change of the model to be used. Our GMW (graph of microworlds) framework effifiently assists a learner in such ‘progressive’ knowledge acquisition by adaptively giving her/him microworlds. A node of GMW has the description of a microworld which includes the model, its modeling assumptions (which can explain why the model is valid in the situation) and the tasks through which one can understand the model. The GMW, therefore, can adaptively provide a learner with the microworld and the relevant tasks to understanding it. An edge has the description of the difference/change between microworlds. The GMW, therefore, can provide the relevant tasks which encourage a learner to transfer to the next microworld and can explain how/why the behavioral change of the model is caused by the change of the situation in model-based way. This capability of GMW greatly helps a learner progressively refine, that is, reconstruct her/his knowledge in a concrete context. Tomoya Horiguchi* Tsukasa Hirashima** *Faculty of Maritime Sciences, Kobe University **Deptartment of Information Engineering, Hiroshima University