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  Published Paper Details:

  Paper Title

AI BASED AUTOMATED COURSE GENERATOR USING MERN STACK FOR E-LEARNING CONTENT

  Authors

  Anusha G,  Deepti G Padaki,  Hadiah Tasneem,  G A Sinchana

  Keywords

Artificial Intelligence, MERN Stack, E-Learning, Automated Content Generation, Chatbot, Personalized Learning

  Abstract


With the rapid expansion of digital education, designing structured and standardized academic courses manually has become time-consuming and inefficient. This project presents an AI-based Course Generator developed using the MERN stack (MongoDB, Express.js, React.js, and Node.js) to automate the creation and management of course structures. The proposed system generates course outlines, modules, learning objectives, and assessment plans based on predefined rules, templates, and user-selected parameters such as subject, academic level, duration, and difficulty. The application provides an interactive web interface for instructors and administrators to design, customize, and manage courses efficiently. MongoDB is used for storing course templates and user data, while React ensures a responsive user experience. The system improves consistency, reduces manual workload, and enables scalable course generation without relying on advanced language models or natural language processing techniques. This approach makes the solution cost-effective, transparent, and suitable for educational institutions and training platforms seeking structured course development.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2512505

  Paper ID - 298865

  Page Number(s) - e396-e403

  Pubished in - Volume 13 | Issue 12 | December 2025

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Anusha G,  Deepti G Padaki,  Hadiah Tasneem,  G A Sinchana,   "AI BASED AUTOMATED COURSE GENERATOR USING MERN STACK FOR E-LEARNING CONTENT", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 12, pp.e396-e403, December 2025, Available at :http://www.ijcrt.org/papers/IJCRT2512505.pdf

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Call For Paper December 2025
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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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