Learning Persian grammar with the aid of an intelligent feedback generator

摘要

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.