Advanced International Journal for Research

E-ISSN: 3048-7641   •   Impact Factor: 9.11

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Design and Implementation of an Automated MCQ Generator using NLP

Author(s) Himalakshi Das
Country India
Abstract Multiple Choice Questions are widely used for the assessment of candidates in many competitive examinations. In educational institutions, course instructors conduct class tests by providing question papers with MCQs to examine student’s understanding of the course. Preparing MCQs manually across different fields or domains is a challenging and time-consuming task that requires significant brainstorming. The automatic generation of multiple-choice questions using Natural Language Processing (NLP) has emerged as prominent research area among computing scientists. Automatic MCQ generation is a challenging task, as it requires generating relevant, semantically valid and contextually correct questions from a given text. Accurate context understanding is crucial for generating relevant and meaningful questions. The proposed system is designed to automatically generate MCQs from a given text. State-of-the-art Natural Language Processing (NLP) techniques are used to design the system. The proposed system accepts a textual passage as input and automatically generates a set of MCQs based on the content. The proposed system analyzes the document to obtain a summarized version of the passage and extracts keywords for generating relevant questions. In the proposed system, the identified keywords function as answer candidates for the MCQs. The generated MCQs follow a fill-in-the-blank format. The proposed system also generates distractors to provide additional answer options alongside the correct response. The implementation of the automated MCQ generator is carried out in Python, utilizing NLP libraries for text processing, keyword extraction and question generation.
Keywords Natural Language Processing, NLP, Multiple Choice Questions, MCQ , Bidirectional Encoder Representation from Transformer, BERT, Python Keyword Extractor,PKE
Field Computer
Published In Volume 7, Issue 1, January-February 2026
Published On 2026-02-23
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E-ISSN 3048-7641
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