A Survey on Development Approaches for Automated MCQ Generator Using Natural Language Processing
Abstract
Within the field of education, it is widely acknowledged that posing questions to learners at the end of a lesson is an effective teaching strategy. For cost-saving reasons, especially when there are multiple candidates, the majority of educational institutions and have made multiple-choice questioning (MCQ) the mainstay of their testing procedures. In Natural Language Processing (NLP), the task of autonomously generating multiple-choice questions is both beneficial and challenging. It involves using textual information to automatically generate relevant and accurate queries. Teachers find it stressful and challenging to manually generate meaningful, significant, and relevant questions, despite its importance. In our project, we describe an NLP-based method for producing MCQs on its own. Natural language processing (NLP) is an artificial intelligence field that studies how humans and computers interact with natural language. Our approach places a strong emphasis on using natural language processing (NLP) to set up multiple choice questions (MCQs). This improves the process of creating and modifying MCQs and creates a useful question bank that academics can use later on with their students. This will ensure that the multiple-choice questions (MCQ) contain options and questions relevant to the learning objectives.
Keywords
Multiple Choice Questions, Natural Language Processing, Distractor Generation, Summary Generation, Automated Question Generation
Citations
IRE Journals:
Aditya Sangwai , Aditya Agrawal , Prasad Patil , Mandar Kulkarni , Dr. Anupama Phakatkar
"A Survey on Development Approaches for Automated MCQ Generator Using Natural Language Processing" Iconic Research And Engineering Journals Volume 7 Issue 9 2024 Page 1-5
IEEE:
Aditya Sangwai , Aditya Agrawal , Prasad Patil , Mandar Kulkarni , Dr. Anupama Phakatkar
"A Survey on Development Approaches for Automated MCQ Generator Using Natural Language Processing" Iconic Research And Engineering Journals, 7(9)
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