Cognitive analysis for representation change

The rep2rep project is developing an AI tool to automatically select an appropriate representation to solve a particular problem for a particular person. A prerequisite of this tool is to understand (i.e., model) how a reader interprets a representation. But interpretations can vary wildly between novices and experts, readers of similar ability, or even the same reader in different tasks. We present a theory and notation (RIST and RISN) for analysing the cognitive features of a representation's interpretation, and introduce a web app to construct RISN models. These models provide information about cognitive properties of representations to guide automated representation selection to support human problem solving.