This paper attempts to describe how an intelligent feedback generator (IFG) is designed, and implemented to help learners of Persian. Keeping this goal in mind to design the system effectively, a collection of information is initially gathered to find what areas are most difficult for such learners. By employing two natural language processing engines for Persian and English, a feedback generator has been created. The framework meets expectations by comparing logical structures originated from English and Persian sentences. Anomaly detection is done via comparing these logical structures. With a few adjustments, the system can also be used with Persian learners of English since it can parse input from both languages. Major areas of difficulty for learning Persian grammar have been identified.A parser is developed to parse basic aspects of both Persian and English grammar.Students are exposed to the system to test the grammatical correctness.Students' output is processed and analyzed.Relevant corrective feedback is generated and displayed to the students.
['Vahid Reza Mirzaeian', 'Hamedreza Kohzadi', 'Fatemeh Azizmohammadi']
Learning Persian grammar with the aid of an intelligent feedback generator