Intelligent Tutoring Systems (ITSs) are complex computer programs that manage various heterogeneous types of knowledge ranging from domain to pedagogical knowledge. ITS aims to overcome some educational problems concerning individual differences, capabilities and skills. So, the recognized leadership in the learning process is centered on the student himself. This research is adopting on the Natural Language processing and intelligent agents in this Intelligent Tutoring Systems. In fact, the resources needed to build an ITS come from multiple research fields, including artificial intelligence, the cognitive sciences, education, human-computer interaction and software engineering. With the aid of Natural Language Processing (N.L.P.), we can deal with the student in analyzing his answers and solving the questions, especially that this research concentrates on the basics of the grammar of the Arabic language as domain knowledge. The global structure of ITS consists of mainly four modules: a tutor module, a question selector, an expert module and a student module. This research concentrates on the Expert Module (E.M.) that aims to get the correct answer of a specific question from the domain. The E.M. receives a question that is selected randomly by the question selector from a question bank. Such a question is represented to the student using Arabic language. The E. M. analyzes that question by consulting a dictionary which contains a lot of Arabic words with related features. The E.M. generates the appropriate answer by matching the relating features of that question words.
Mona Hafez Mahmoud, Electronic Research Institute, Egypt
Sanaa Hassan Abo El-Hamayed, Electronic Research Institute, Egypt
Stream: Primary and secondary education
This paper is part of the ACEID2015 Conference Proceedings (View)
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