The Use of Artificial Intelligence Models in the Automated Knowledge Assessment System

A functional structure of an intellectual system of linguistic analysis of a deployed text response utilizing models of artificial intelligence has been developed and tested in this research paper. An algorithm of fuzzy semantic comparison of textual information—answers to questions submitted by a student in natural language, with options of correct answers, which formalizes description of linguistic structure of the study content and answers has been elaborated. The algorithm provides automatic conversion of student’s responses from a natural language into an intersystem form, the formation of lexical units of the text, followed by the implementation of morphologic, syntactic, semantic and pragmatic analysis. Models of artificial intelligence to compare textual information in content are used on the stages of semantic and pragmatic analysis. As a result of the semantic analysis a semantic network is grounded—a framework for knowledge representation in the form of nodes connected by arcs (links). In the pragmatic analysis it is determined whether a response belongs to a particular subject area. These stages are proposed for implementation through the use of neural networks. The advantage of using neural networks is their versatility. The permanent structure for the neural network can be adapted (trained) to compare texts from various subject areas. In contrast to the known methods of semantic and pragmatic analysis algorithms based on artificial intelligence models will provide more opportunities to inspect automated text responses given in free text form in natural language with greater certainty.