Abstract: Traditional manual study methods in academic environments suffer from operational deficiencies, temporal consumption, and lack of personalization. This paper proposes the AI-Based Study Assistant, an intelligent educational platform leveraging natural language processing and machine learning. The system utilizes NLTK and spaCy for automated text summarization and question generation from uploaded study materials. A Flask web architecture integrated with SQLite database provides real-time quiz generation and performance analytics. The framework automatically creates flashcards, summaries, and multiple-choice questions from PDF, DOCX, and TXT files, achieving contextual relevance exceeding 92%. An intelligent reminder system operates via background threading, sending email notifications for consistent study habits. Experimental results indicate significant reduction in study preparation overhead and enhanced learning retention through personalized assessment generation.
Keywords: Artificial Intelligence, Natural Language Processing, Intelligent Tutoring Systems, Automated Quiz Generation, Personalized Learning, Flask Framework, Educational Technology, Machine Learning, Study Management, Performance Analytics
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DOI:
10.17148/IJARCCE.2026.15180
[1] Archana P, Thanuja J.C, "AI-BASED STUDY ASSISTANT: AN INTELLIGENT FRAMEWORK FOR PERSONALIZED LEARNING AND AUTOMATED ACADEMIC ASSESSMENT.," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.15180
