Implementation of Decision-making Methods in Intelligent Automated Educational System Focused on Complete Individualization in Learning

Abstract

To solve a problem of individualization in learning based on Intelligent Automated Educational Systems (IAES) involves to devise special methods of decision-making. In this article we propose to implement a complete individualization in learning (assessment, individual learning path management, adaptation of the curriculum and test sampling, the synthesis of man-machine dialog) by means of afference process simulation. It is considered the problem of searching for a compromise of goals between the models of a student, a teacher and a tutor within the base of the current learning environment. To this effect it is proposed a four-stage IAES-based decision-making scheme and synthesis mechanism of Cognitive Maps of Knowledge Diagnostic (CMKD). The problems of CMKD synthesis and visualization is considered. In conclusion, the results of approbation the proposed technologies in learning are provided.