Paper Title
AI-BASED PERSONALIZED STUDY PLAN GENERATOR USING MACHINE LEARNING AND LARGE LANGUAGE MODELS
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Registration ID: IJNRD_323109
Published ID: IJNRD2604521
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Keywords
Artificial Intelligence, Machine Learning, Large Language Models, Personalized Study Planning, Educational Technology, Intelligent Tutoring Systems, Learning Analytics, Study Plan Generation, Diagnostic Assessment, Adaptive Scheduling.
Abstract
Artificial Intelligence has significantly transformed the education sector by enabling personalized and adaptive learning experiences. Traditional study methods often follow a uniform approach, failing to consider individual differences in learning pace, strengths, weaknesses, and time availability. Such one-size-fits-all schedules can lead to inefficient learning and reduced academic performance. To overcome these limitations, this paper proposes an AI-Based Personalized Study Plan Generator that leverages Large Language Models (LLMs) to create dynamic and interactive learning schedules. The system begins by collecting user inputs such as the target subject and exam date, and then generates a diagnostic quiz tailored to the learner’s level to assess prior knowledge and identify gaps. Based on the quiz performance, the system provides instant evaluation, detailed feedback, and concept-wise analysis. It then generates a customized day-by-day study plan incorporating effective learning strategies such as spaced repetition and active recall. Additionally, the system performs continuous progress tracking and periodically updates the schedule to improve learning efficiency. The proposed approach enhances student engagement, optimizes study time, and provides a scalable solution for personalized education, making it highly suitable for modern AI-driven learning environments.
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How To Cite (APA)
Lingala Pallavi, Chippalapally Srinath Reddy, Kokonda Harshitha, & B. Dharani (April-2026). AI-BASED PERSONALIZED STUDY PLAN GENERATOR USING MACHINE LEARNING AND LARGE LANGUAGE MODELS. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(4), f149-f151. https://ijnrd.org/papers/IJNRD2604521.pdf
Issue
Volume 11 Issue 4, April-2026
Pages : f149-f151
Other Publication Details
Paper Reg. ID: IJNRD_323109
Published Paper Id: IJNRD2604521
Research Area: Other area not in list
Author Type: Indian Author
Country: Hyderabad, Telangana, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2604521.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2604521
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