AI-Powered Career Guidance Chatbot Using Retrieval-Augmented Generation for First-Year Students

Abstract

This report presents the design and implementation of an AI-powered career guidance chatbot for first-year university students. The system leverages Retrieval-Augmented Generation (RAG) to combine large language models with a curated knowledge base of alumni experiences, ensuring accurate, relevant, and context-aware responses. The chatbot enables students to access authentic career insights, understand job market trends, and explore professional paths through an interactive conversational interface. By integrating natural language processing and vector-based information retrieval, the system delivers personalized guidance tailored to individual user queries. The proposed solution addresses the gap between students and alumni knowledge by providing scalable, AI-driven access to real-world experiences. Benchmark results from the literature indicate that RAG-based systems achieve 34% higher factual accuracy and 62% fewer hallucinations compared to standard LLMs, while alumni-data-driven systems improve student career awareness by 41%. This work was conducted at Arab International University (AIU), Syria . Official University Website:https://www.aiu.edu.sy

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