scholarly journals A Fuzzy Expert System Architecture for Intelligent Tutoring Systems: A Cognitive Mapping Approach

2012 ◽  
Vol 04 (01) ◽  
pp. 29-40 ◽  
Author(s):  
Mohammad Hossein Fazel Zarandi ◽  
Mahdi Khademian ◽  
Behrouz Minaei-Bidgoli ◽  
Ismail Burhan Türkşen
Author(s):  
Javier Gonzalez-Sanchez ◽  
Maria Elena Chavez-Echeagaray ◽  
Kurt VanLehn ◽  
Winslow Burleson ◽  
Sylvie Girard ◽  
...  

Author(s):  
Hafidi Mohamed ◽  
Bensebaa Taher

This paper describes an adaptive and intelligent tutoring system (AITS) based on multiple intelligences and expert system. Most of adaptive and intelligent tutoring systems based their adaptation to user’s skill level. Other learner features taken into account are background, hyperspace experience, preferences and interests. However, less attention was paid to multiple intelligences and their effects on learning. Moreover, to design AITS which can manage both different disciplinary domains and a guide for the learner is difficult. The specialization of the analysis treatments is responsible for the loss of reusability for the other disciplinary domains. To overcome these limitations, the authors will try to combine the benefits of paradigms (adaptive hypermedia, intelligent tutoring system, multiple intelligences) in order to adapt the course to the needs and intellectual abilities of each learner.


1991 ◽  
Vol 24 (6) ◽  
pp. 307-314 ◽  
Author(s):  
A. G. Collins ◽  
J. Searleman ◽  
K. J. Collins

An expert system has been developed to aid the operators of small water treatment plants. A tutorial component of the expert system explains the possible reasons for common problems by focusing on the jar test analysis for chemical dosage control. The tutor provides an operator with the opportunity to run the jar test, receive feedback on the parameters selected, visualize the results on the actual water treatment processes, and be tutored in the topics related to understanding the processes involved and additional supplemental areas such as concentrations and conversions. A background of Intelligent Tutoring Systems, along with a justification of the approach, is provided. The development of the jar test tutor including knowledge representation is described.


2000 ◽  
Author(s):  
Christine Mitchel ◽  
Alan Chappell ◽  
W. Gray ◽  
Alex Quinn ◽  
David Thurman

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