Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{200232,
author = {VISHAL K K and RINESH MENON R and VIGNESHWARAN R and YASWANTH NETHAJI A and PONNEELA VIGNESH R},
title = {A COGNITIVE - AWARE AI FRAMEWORK FOR PERSONALIZED LEARNING SUPPORT},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {12},
number = {12},
pages = {3285-3293},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=200232},
abstract = {In today's competitive academic environment, students are required to study for extended periods, which often leads to cognitive fatigue and reduced learning efficiency. Traditional learning systems fail to monitor student mental state, resulting in decreased productivity and ineffective study sessions. To address this issue, this project proposes a Personal AI Study Coach with Cognitive Fatigue Detection that provides intelligent and adaptive learning assistance.
The system monitors student performance in real time and analyzes various parameters such as response time, error rate, question difficulty handling, and self-reported fatigue. Based on these inputs, the system determines the cognitive fatigue level and dynamically adjusts the learning process. When fatigue is detected, the system recommends recovery strategies including short breaks, revision sessions, or reduced difficulty questions. The application also includes adaptive quiz generation, weak topic identification, spaced repetition learning, AI-powered chat assistance, and performance analytics dashboard. The backend is implemented using FastAPI, while SQLite is used for database storage. The proposed system improves learning effectiveness, reduces burnout, and provides personalized study experience for students. The system also incorporates performance analytics to identify learning patterns and predict optimal study times.},
keywords = {Artificial Intelligence, Cognitive Fatigue Detection, Adaptive Learning, FastAPI, SQLite, Machine Learning, Study Coach, Smart Learning System.},
month = {May},
}
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