Symbolic assessment of free text answers in a second-language tutoring system

We present an approach to Computer-Assisted Assessment of free-text material based on symbolic analysis of student input. The theory that underlies this approach arises from previous work on DidaLect, a tutoring system for second-language reading skill enhancement. The theory enables the processing of free-text segments for assessment to operate without preencoded reference material. A study based on a corpus of 48 student answers to several types of questions has justified our approach, helped define a methodology and design a prototype.