Authors :
Dr. Sathish Kumar; Sandeep H T; Siva Prasath V; Vishal Veeru B; Vishnu Nivasini J
Volume/Issue :
Volume 10 - 2025, Issue 4 - April
Google Scholar :
https://tinyurl.com/c5v93xkx
Scribd :
https://tinyurl.com/3rc8rv75
DOI :
https://doi.org/10.38124/ijisrt/25apr1686
Google Scholar
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Abstract :
Modern education often lacks the personalized support needed to address individual learning styles and academic
challenges. This project presents an AI-powered personalized learning assistant that combines intelligent tutoring,
automated summarization, and grade prediction to support self-guided learning. The system utilizes advanced AI models
for natural language understanding, document analysis, and performance forecasting to adapt responses and content
delivery to each learner. AI integration facilitates real-time explanations, concise PDF-based note generation, and interactive
learning feedback. These features streamline the study process, reduce cognitive load, and promote deeper understanding
through customized assistance. Additionally, the assistant applied machine learning techniques to track learning patterns
and improve their recommendations over time, creating a dynamic and evolving support system. Emphasizing on usability
and learner-centric design, the assistant aims to close the gap between technology and effective study habits, encouraging
autonomy, academic confidence, and knowledge retention. The development, deployment, and evaluation of this system are
explored in this study, highlighting its potential as a transformative educational tool.
References :
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- Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264-75278.
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- Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic Review of Research on Artificial Intelligence Applications in Higher Education. International Journal of Educational Technology in Higher Education, 16(1), 1-27.
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Modern education often lacks the personalized support needed to address individual learning styles and academic
challenges. This project presents an AI-powered personalized learning assistant that combines intelligent tutoring,
automated summarization, and grade prediction to support self-guided learning. The system utilizes advanced AI models
for natural language understanding, document analysis, and performance forecasting to adapt responses and content
delivery to each learner. AI integration facilitates real-time explanations, concise PDF-based note generation, and interactive
learning feedback. These features streamline the study process, reduce cognitive load, and promote deeper understanding
through customized assistance. Additionally, the assistant applied machine learning techniques to track learning patterns
and improve their recommendations over time, creating a dynamic and evolving support system. Emphasizing on usability
and learner-centric design, the assistant aims to close the gap between technology and effective study habits, encouraging
autonomy, academic confidence, and knowledge retention. The development, deployment, and evaluation of this system are
explored in this study, highlighting its potential as a transformative educational tool.