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  Published Paper Details:

  Paper Title

AI-Based Personalized Learning Platform for Students and Faculty

  Authors

  Prof. Said S. K.,  Belhekar Vaishnavi Goraksha,  Doke Snehal Raychand,  Chikhale Pranjal Santosh,  Pavale Trupti Bapusaheb

  Keywords

Artificial Intelligence, Personalized Learning, Adaptive Education System, Machine Learning, Quiz-Based Progress Analysis, Faculty Dashboard, Student Analytics.

  Abstract


The AI-Based Personalized Learning Platform integrates Artificial Intelligence, Machine Learning, and Data Analytics to revolutionize the education experience for both students and faculty. The system personalizes learning pathways by continuously analyzing quiz performance, engagement patterns, and topic comprehension levels. Using an intelligent quiz-based progress analysis model, it dynamically adjusts the difficulty of study materials and recommends additional content to address weak areas. Faculty members gain access to real-time student progress dashboards, enabling data-driven teaching decisions and individualized mentoring. The platform also incorporates Natural Language Processing (NLP)-based feedback and automated content summarization, helping students understand complex concepts in simpler terms. By combining adaptive learning, real-time analytics, and AI-guided recommendations, this system enhances academic performance, student engagement, and overall learning efficiency in modern educational environments.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2510820

  Paper ID - 295984

  Page Number(s) - h41-h46

  Pubished in - Volume 13 | Issue 10 | October 2025

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Prof. Said S. K.,  Belhekar Vaishnavi Goraksha,  Doke Snehal Raychand,  Chikhale Pranjal Santosh,  Pavale Trupti Bapusaheb,   "AI-Based Personalized Learning Platform for Students and Faculty", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 10, pp.h41-h46, October 2025, Available at :http://www.ijcrt.org/papers/IJCRT2510820.pdf

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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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