Towards a Knowledge-based Free-text Response Assessment System

In the present work, the architecture of a knowledge-based free-text response assessment system is presented, which can assess free-text responses on open-ended questions based on text comprehension theories. Its main advantages are the facts of extending the knowledge base and assessing responses on questions of different types. It is constituted from three basic modules: The first module is the Normalization Module (NoM), which is responsible for converting free-text responses into normalized responses, as well as, converting technical text into “functional system”. The second module is the Functional System Module (FSM), which depicts all entities of a technical text and the relations among them, and is presented, by the representation of microstructure and macrostructure of a Computer Networks domain technical text, according to Denhiere-Baudet Text Comprehension Model. The third module is the Assessment Module (AM), responsible for assessing the normalized responses. It is based on data, obtained by experimental studies on microstructure and macrostructure, constructed by secondary school students, during reading technical texts and responding to questions.