Intelligent Tutoring Systems (ITS) can both help improve student learning and serve as useful platforms for experiments in learning science [1,2]. But the difficulty of building or customizing ITSs has hindered their acceptance among educators and researchers [3]. The Cognitive Tutor Authoring Tools (CTAT) project aims to provide a suite of authoring tools that make tutor development more affordable by leveraging human-computer interaction and artificial intelligence techniques. Previous efforts on CTAT added the capability for nonprogrammers to create exampletracing tutors via a programming-by-demonstration technique that requires no coding [4]. While exampletracing tutors provide a student experience similar to that of the more general cognitive tutors, they also require that an author demonstrate and fully annotate each individual problem to be presented.