Publication

Abstract : The significance of e-learning technologies has increased rapidly in recent times. With the advent of data from Educational Data Mining applications, public datasets, social media, the design and implementation of intelligent tutoring systems involving adaptive pedagogical strategies and student modelling have become much easier. There are many Intelligent Tutoring Systems [ITS] available in various domains including STEM areas to language learning. In this paper, we present an ITS for learning English Punctuation which provides personalized hints to the students based on the incorrect attempts they make. System brings in automation in presenting the exercises to the students by the use of template structures. The domain knowledge of the system is modeled using syntactic and semantic components of English Language. The knowledge state of the student is captured by the system based on the number of attempts and the time they take to solve an exercise. Pre-test and Post-test analysis has been performed to measure the effectiveness of the system.