Multiple Representations for STEM subjects - applications from the learning sciences

Graphs, diagrams, formulae, numbers and verbal descriptions form the vocabulary of STEM experts in describing phenomena encountered either in the laboratory or the natural world. Whereas students of STEM disciplines might form various internal representations that constitute their memory and comprehension of knowledge structure, as instructors we must often rely on the external representations they share with us through written exercises or examination scripts as evidence of their learning. In this talk, I shall present my perspective on the value of multiple representations from a SoTL study in introductory physics at a regional public university in the United States and explore a special case of an established active learning technique (Interactive Lecture Demonstrations) to foster student learning in this area. I shall reference the learning sciences framework from How People Learn (1999), the physics education research literature and tie into recent European work on orchestration from the field of computer supported collaborative learning (CSCL).