In this talk I will describe ongoing efforts at Kansas State University to utilize physical and virtual representations of simple machines and to assess their impact on learning in a conceptual physics class. I will also describe studies with students in a calculus-based physics course to facilitate transfer of problem solving skills across problems using graphical, functional and numerical representations.
Results from both studies have helped highlight the affordances and constraints provided by various representations. Our results also show interesting sequencing effects when more than one representation is used in learning and problem solving.