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Intelligent-based Career Guidance Information Management

Year: 2026

Type: article

Abstract: This study develops a computerized career guidance information management system to overcome the limitations of traditional career counseling methods, which often lack accessibility, real-time updates, and personalization. The system uses AI and ML to provide tailored career recommendations based on users’ skills, interests, and questionnaire responses. The web-based platform, implemented using Python (Flask, TensorFlow) for the backend and HTML, CSS, and JavaScript for the frontend, features user registration, skill selection, and dynamic recommendation refinement through questionnaires. The recommendation engine employs machine learning algorithms to deliver accurate, adaptive career suggestions. This research bridges the gap between conventional counseling and modern technologies, offering a scalable, data-driven career guidance solution. This study highlights the potential of AI-powered systems to provide personalized, accessible, and efficient career advice in alignment with digital education advancements

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.20735223

Authors: Egete, D. O., Ele, B. I., Ashishie, D. U., Omini, E. O., Isong, C. P.

Institution: University of Calabar

Language: English

Topic: Edcuational Technology Systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7165058213

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