Aitut – An AI-Based Intelligent Tutoring and Mentorship Platform

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Authors: Neha Kulkarni, Anjali Katta, Yogesh Mane, Prof. Ganesh P. Buchade Nagraj Nandal
Cited by: 0

Abstract

Traditional educational systems struggle with rigid curricula and limited personalization, resulting in significant employability gaps where only 42.6% of Indian graduates meet industry standards. Current platforms lack integration of adaptive tutoring, real-time mentorship, and career guidance within accessible online/offline frameworks. This paper presents AI-TUT, a comprehensive AI-driven platform that analyzes learner behavior through machine learning to deliver customized study paths, performance analytics, mentorship matching, and employability tools including mock interviews. The system employs React Native frontend, FastAPI backend, and LangChain-powered AI models with MongoDB storage. Experimental evaluation with 150 undergraduates demonstrates 28% higher skill proficiency and 35% improved interview performance compared to traditional methods, validating AI-TUT's potential to transform higher education through scalable, equitable learning solutions

Fields of Study & Subjects

Intelligent Tutoring Systems and Adaptive Learning Artificial Intelligence in Education Edcuational Technology Systems

Publication details

Journal / source
International Journal of Advanced Research in Science Communication and Technology
Pages
138–138
Publication date
15 January 2026