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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM45572
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
â 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 levelsâsuch as knowledge recall, application, and analysis. Additionally, each question is accompanied by a corresponding answer key, which helps educators expedite the evaluation process.
KEYWORDS
Publication Date
4/23/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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