Intelligent Tutoring System for Evaluating Student Performance in Descriptive Answers Using Natural Language Processing

Computer Assisted Assessment of free-text answers has established a great deal of work during the last years due to the need of evaluating the deep understanding of the lessons concepts that, according to most educators and researchers, cannot be done by simple MCQ testing. In this paper we have reviewed the techniques underpinned this system, the description of currently available systems for marking short free text response and finally proposed a system that would evaluate the descriptive type answers using Natural Language Processing and lastly compared the results obtain by human graders and proposed system. We have also compared the results of proposed system with existing systems.