Nowadays, Intelligent Tutoring Systems (ITSs) are so regarded in order to improve education quality via new technologies in this area. One of the problems is that the language of ITSs is different from the learner’s. It forces the learners to learn the system language. This paper tries to remove this necessity by using an Automatic Translator Component in system structure like Google Translate API.
This system carry out a pre-test and post-test by using Expert System and Jackson Model before and after of training a concept. It constantly updates learner model to save all changes in learning process. So this paper offers an E-Learning system which is web-based, intelligent, adaptive, multilingual and remotely accessible where tutors and learners can have non-identical language. It is also applicable Every Time and Every Where (ETEW). Furthermore, it trains the concepts in the best method with any language and low cost.
Source: Cornell University
Authors: Hossein Movafegh Ghadirli | Maryam Rastgarpour
Distributed Case Based Reasoning for Intelligent Tutoring System
Intelligent Student Profiling with Fuzzy Models
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