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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM45572

Question Generation Using Artificial Intelligence and Knowledge Augmented Generation

Stream/Area:

-

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Paper ID:

IJSREM45572

Volume:

9 |

4 |

Apr 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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10.55041/ijsrem45572

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Abstract

– This project introduces an innovative, AI-driven platform tailored to streamline and enhance the process of question paper generation for educators at various academic levels. Utilizing cutting-edge technologies such as Natural Language Processing (NLP), Knowledge-Augmented Generation (KAG), and Large Language Models (LLMs), the system is capable of understanding and extracting key concepts from a variety of educational resources. These include user-uploaded materials such as textbooks, existing question banks, lecture notes, and previous year exam papers. Educators are provided with a user-friendly interface where they can define specific parameters, including subject area, topic coverage, question complexity (difficulty level), and the desired number of questions. Based on these inputs, the platform intelligently generates a diverse and balanced set of questions, ensuring coverage across cognitive levels—such as knowledge recall, application, and analysis. Additionally, each question is accompanied by a corresponding answer key, which helps educators expedite the evaluation process.

KEYWORDS

– Automated Question Paper Generation NLP-Based Assessment Design Tool AI-Powered Educational Assessment System

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4/23/2025

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The authors declare no conflict of interest related to this research work.

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