Free Text Response Assessment System Based on a Text Comprehension Model

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Knowledge representation for an automated normalized answers assessment system, based on text comprehension theories

In the present work, a knowledge representation of Computer Networks technical text, according to the Denhiere-Baudet text comprehension model, is presented. The semantic relations among units and events of a technical text can be expressed by, structures, as microstructure and macrostructure. Furthermore, the explicit and implicit knowledge representation, and the micro and macrostructure representation of the functional system operations, depicted in this text, is provided. The presented methodology can support automated reasoning, through the knowledge representation, which leads to automated knowledge extraction from a technical text, and, subsequentially, to automated normalized answers assessment

How Concept Mapping Can Support Technical Systems Understanding Based on Denhiere-Baudet Text Comprehension Model

This paper presents a study aiming to investigate the way in which concept mapping could assist students to improve their technical systems understanding concerning Computer Science, on the basis of Denhiere-Baudet text comprehension model structures. The results of the study indicate that concept mapping supports students in two levels: (i) those, who have superficial comprehension on the underlying concepts and represent satisfactorily microstructure, and (ii) those, who have deeper comprehension on that concepts and attributed satisfactorily to the teleology

Semandix: Constructing a Knowledge Base According to a Text Comprehension Model

The current chapter presents a computational semantic tool called Semandix, which is based on a cognitive text comprehension model. The basic aim of this tool is to construct a semantic knowledge base of concepts and relations among them, in order to analyze free text responses, assess concept maps and provide a semantic dictionary of concepts categorized according to the structures of that cognitive model. Thus, its basic modules are: the ‘Semantic Dictionary’, the ‘Text Analyzer’, the ‘Concept Map Assessor’, and the ‘Administrator’. The enrichment of Semandix knowledge base is being realized through XML format files, extracted from concept mapping tools, as CmapTools, and ‘machine-readable’ dictionaries, as WordNet through the Visdic Editor. So far, Semandix implements some of the basic modules of a proposed free-text response assessment system. Future plans are the Semandix extension, in order to implement the other modules of the proposed system, and the formalization of the semantic content constructed to enrich its knowledge base