A Framework for Developing Intelligent Tutoring Systems Based on Domain Models in the Form of Decision Trees

被引：0

作者：

Krygin, A. I. ^{[1
]}

Gumerov, M. R. ^{[1
]}

Moskalenko, N. A. ^{[1
]}

Sychev, O. A. ^{[1
]}

机构：

[1] Volgograd State Tech Univ, Fac Elect & Comp Engn, Volgograd 400005, Russia

来源：

PATTERN RECOGNITION AND IMAGE ANALYSIS | 2024年 / 34卷 / 03期

关键词：

decision trees; intelligent tutoring systems; domain models; framework;

D O I：

10.1134/S1054661824700561

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Formal domain models make it possible to build intelligent tutoring systems based on symbolic artificial intelligence that are capable of reliable error detection, generation of explanatory feedback and pedagogical questions, etc. However, developing these models for modern inference engines is a very time-consuming problem. This paper describes a method for representing domain problems and solutions in the form of decision trees and proposes a prototype framework for developing intelligent tutoring systems based on it. During the experimental development of four kernels for intelligent tutoring systems, the framework showed moderate performance, providing a significant reduction in development time.

引用

页码：710 / 716

页数：7

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