Research on Knowledge-Based Intelligent Tutoring System

2011 ◽  
Vol 55-57 ◽  
pp. 1424-1429
Author(s):  
Zhen Zhen Yi ◽  
Ke Zhao ◽  
Ya Tao Li ◽  
Wei Xu

Aiming at students’ learning process, and based on the analysis of tutorship rules of students’ learning after class, a Knowledge-Based Intelligent Tutoring System is given. The system comprehensively uses agent technology, the knowledge-based automatic reasoning, resource modeling for knowledge classification, field natural language understanding, data mining, computer networks, databases and other technologies. It creates a student-oriented self-motivated learning environment in which students can learn abundant knowledge of one or many subjects, send the problems encountered in their own learning to the system server by network, and get real-time multiple tutorship information as an excellent teacher do.

2014 ◽  
Vol 3 (2) ◽  
pp. 56-74
Author(s):  
Sarah E. Schultz ◽  
Ivon Arroyo

Two major goals in Educational Data Mining are determining students' state of knowledge and determining their affective state as students progress through the learning session. While many models and solutions have been explored for each of these problems, relatively little work has been done on examining these states in parallel, even though the psychology literature suggests that it is an interplay of both of these states that influences how a student performs and behaves. This work proposes a model that takes into account the performance and behavior of students when working with an Intelligent Tutoring System in order to track both knowledge and engagement and tests it on data from two different systems and explores the usefulness of such models.


2011 ◽  
Vol 55-57 ◽  
pp. 767-772 ◽  
Author(s):  
Ya Tao Li ◽  
Ke Zhao ◽  
Zhen Zhen Yi ◽  
Pei Tao Cheng

The traditional intelligent tutoring system as a web-based education tools used for adaptive learning can’t solve the encountered question in time while the student is learning with the absence of nature language understanding system. In this paper, a web-based intelligent tutoring system is firstly introduced to solve the encountered question in real time. Secondly, a concept model representing the concept connotation, the extension and the relation between them is presented to support the nature language understanding system in order to extract the question’s meaning. Furthermore, a knowledge representation of verb and noun in impersonal mature domain is involved. Thirdly, the semantic processing arithmetic of the verb phase is given. Finally, the result of experiment and application of arithmetic are shown.


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