Understanding students' explanations in geometry tutoring

Abstract

Precise Natural Language Understanding is needed in Geometry Tutoring to accurately determine the semantic content of students' explanations. The paper presents an NLU system developed in the context of the Geometry Explanation Tutor. The system combines unification-based syntactic processing with description logics based semantics to achieve the necessary accuracy level. Solutions to specific semantic problems dealing with equivalence of semantic representations are described. Experimental results on classification accuracy are also presented.