StudyMind Habit analyzer for Multi-Role Educational Environments

StudyMind AI is a full-stack, AI-powered web
application designed to analyze and improve student
study habits in multi-role educational environments.
Leveraging a Flask-based RESTful backend and a
responsive single-page frontend, the system supports
three user roles Administrator, Teacher, and Student
each equipped with purpose-built dashboards and
functionality. The platform integrates the Groq Llama3
8B large language model for intelligent score prediction,
with a deterministic rule-based fallback for offline or
API-limited environments. Core features include real
time study session tracking with a built-in Pomodoro
style timer, teacher-assigned MCQ-based assessments
with automated grading, daily study goal management,
and AI-generated score forecasts with improvement
recommendations. Experimental validation against
manually computed ground truth confirms a prediction
accuracy within 5 percentage points under normal study
patterns. The system demonstrates how lightweight
EdTech solutions can harness state-of-the-art AI
capabilities without heavy infrastructure requirements.