AI-Powered Personalized Learning and Career Enhancement Platform

Abstract

Choosing a suitable career has become increasing obstacle for students in higher secondary and undergraduate programs. Many students find it difficult to identify career paths that align with their interests, psychological traits, and skill levels. Traditional career counselling app methods typically depend on static questionnaires and general recommendations, which often fail to address individual uniqueness. This study proposes an AI-powered personalized learning and career enhancement platform that combines psychological assessment, career recommendation, and adaptive course generation. The system leverages Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to provide intelligent and context-aware guidance. Users are tested through dynamically generated psychological questions designed to identify personality traits and career inclinations across multiple dimensions. Based on the psychological profile and skill-level assessment, the system recommends suitable career paths and generates a customized learning roadmap. Developed using Python and Django, the platform ensures continuous interaction between reasoning models and knowledge retrieval mechanisms. The proposed solution Aims to improve career clarity and learning efficiency through end-to-end personalization.