Objective Type Question Generation using Natural Language Processing

• Published in: International journal of advanced computer science & applications Vol. 13; no. 2
• Main Authors: Deena, G., Raja, K.
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 2022
• Subjects: Natural language processing; Questions; Speech recognition; Teachers
• DOI: 10.14569/IJACSA.2022.0130263
• ISSN: 2158-107X

Automatic Question Generation (AQG) is a research trend that enables teachers to create assessments with greater efficiency in right set of questions from the study material. Today's educational institutions require a powerful tool to correctly assess learner’s mastery of concepts learned through study materials. Objective type questions are an excellent method of assessing a learner's topic understanding in learning process, based on Information and Communication Technology (ICT) and Intelligent Tutoring Systems (ITS).Creating a set of questions for assessment can take a significant amount of time for teachers, and obtaining questions from external sources such as assessment books or question banks may not be relevant to the content covered by students during their studies. This proposed system involves to generate the familiar objective type questions like True or False, ‘Wh’, Fill up with double blank space, match the following type question have generated using Natural Language Processing(NLP) techniquesfrom the given study material. Different rules are created to generate T/F and ‘Wh’ type questions. Dependence parser method has involved in ‘Wh’ questions. Proposed system is tested with Grade V Computer Science text book as an input. Experimental result shows that the proposed system is quite promising to generate the amount of objective type assessment questions.