The AI-Based Career Guidance System is an intelligent advisory platform designed to assist students, early professionals, and career-transitioning individuals in identifying suitable career pathways based on their personality, interests, and long-term goals. The system integrates psychological assessment with AI-driven personalization to enable informed and data-backed career decision-making. The proposed framework comprises two core modules: the Quiz Module and the Guidance Module. The Quiz Module incorporates psychological, behavioral, and aptitude-oriented questions to evaluate a user’s personality traits and career compatibility. Based on the responses, the system categorizes users into distinct personality profiles aligned with relevant career domains. The Guidance Module features an interactive AI chatbot that delivers tailored career advice, comprehensive roadmaps, and actionable steps for achieving specific career goals. It provides insights into required educational qualifications, essential skills, certifications, industry trends, and role progression. Leveraging machine learning and natural language processing, the chatbot delivers context-aware recommendations and adaptive user interactions. A structured and continuously expanding career knowledge base supports the system in providing accurate and reliable information. This work aims to bridge the gap between career uncertainty and clarity by offering a virtual career counselor accessible to all users. By combining psychological profiling with artificial intelligence, the proposed system empowers individuals to discover, plan, and pursue careers that align with their strengths, aspirations, and evolving professional landscapes. The overarching goal is to support graduate students, career changers, and adolescents in exploring both conventional and emerging career opportunities with confidence and direction.
Introduction
The text presents an AI-Based Career Guidance System designed to address the challenges students face in selecting suitable careers amid rapidly evolving industries. Traditional counseling methods are limited in personalization, scalability, and real-time guidance, prompting the development of an intelligent, web-based platform integrating a Personality and Skill-Based Quiz, an AI-powered Chatbot, and Career Roadmaps. The system evaluates users’ skills, interests, and personality traits, provides real-time, context-aware career advice using NLP, and generates structured learning pathways outlining required skills, certifications, and educational steps.
Built on a modular, multi-layered architecture (frontend, backend, AI modules, and database), the system employs ML algorithms, rule-based scoring, and NLP for resume analysis, job-matching, and personalized guidance. Testing demonstrated high recommendation accuracy (88–92%) and positive user feedback, with users appreciating the interactive chatbot and detailed roadmaps. The study highlights the system’s potential to replace traditional counseling methods and empower users to make informed career decisions. Future developments include integration with advanced LLMs, multi-session guidance, dynamic industry updates, and cloud or mobile deployment for wider accessibility.
References
[1] Herath and P. Dissanayake, “New Frontiers in Computer-Assisted Career Guidance,” Journal of Information Technology Education: Research, vol. 23, pp. 89– 108, 2024.
[2] A. B. A. K. Abdulhadi, “Implementing a Web-Based Career Counseling and Guidance System for High School Students,” International Journal of Engineering Research & Technology (IJERT), vol. 10, no. 5, pp. 421–425, 2023.
[3] L. Zhang and Y. Wang, “Design of College Students’ Career Planning Guidance System Based on B/S Three-Tier Architecture,”
[4] Journal of Physics: Conference Series, vol. 1998, no. 1, 2021
[5] A. Sharma, P. Jain, and S. Gupta, “Career Compass: An AI- Powered Career Guidance System Based on Interests, Skills, and Soft Skill Profiling,” TechRxiv, 2023.
[6] A. Ghosh, R. Dey, and S. Majumdar, “C3-IoC: An AI-Based Career Guidance System,” International Journal of Artificial Intelligence in Education, vol. 34, no. 2, pp. 223–237, 2023.
[7] P. Li and X. Zhao, “Design of Career Counselling Information System (CCIS) Integrating Labour Market Data,” Education and Information Technologies, Springer, vol. 29, no. 4, 2024.
[8] H. Al-Mashaqbeh, “A Systematic Study of the Literature on Career Guidance and Decision Support Systems,” Journal of Learning for Development, vol. 10, no. 3, pp. 195–208, 2023.
[9] V. Das and R. Reddy, “Unlocking Futures: A Natural Language Driven Career Prediction System,” arXiv preprint, arXiv:2405.18139, 2024.
[10] H. Liu, J. Tang, and J. Han, “JobComposer: Career Path Optimization via Utility Learning from Online Professional Network Data,” arXiv preprint, arXiv:1809.01062, 2023.
[11] J. L. Holland, Making Vocational Choices: A Theory of Vocational Personalities and Work Environments. Psychological Assessment Resources, 1997.