Modeling for meaningful learning

Abstract

In the first part of the chapter, we argue that the goal of formal education should be meaningful learning. Meaningful learning is necessarily social, collaborative, intentional, authentic, and active. The result of meaningful learning lies in its cognitive residue, the learner' mental model. In the second part of this chapter, we describe different components of individual mental models and collaborative mental models. Mental models are rich, complex, interconnected, interdependent, multi-modal representations of what someone or some group knows. Perhaps the most effective means for fostering the development of mental models is the construction of computational models. We argue that modeling is an essential skill for all disciplines engaging students in meaningful learning. So, the third part of the chapter focuses on how technologies can be used to support students' construction of their own models and theories of how phenomena work. Students can build models of domain knowledge, problems, systems, semantic structures, and thinking while studying. In addition to distinguishing between what is modeled, we also distinguish between kinds of modeling systems (deductive simulations, inductive simulations, qualitative causal models like expert systems, and semantic modeling tools), and their affordances for supporting the construction of mental models. © 2006 Springer.