Unnatural Language Processing an Empirical Study of Multimodal Proof Styles

Computer-based logic proofs are a form ofùnnatural' language in which the process and structure of proof generation can be observed in considerable detail. We have been studying how students respond to multimodal logic teaching, and performance measures have already indicated that students' pre-existing cognitive styles have a signiicant impact on teaching outcome. Furthermore, a large corpus of proofs has been gathered via automatic logging of proof development. This paper applies a series of techniques, including corpus statistical methods, to the proof logs. The results indicate that students' cognitive styles innuence the structure of their logical discourse, via their diiering methods of handling abstract information in diagrams, and transferring information between modalities.