Campus 361 – AI-Integrated Education Management and Career Recommendation System
Nigila, P R and Ramola, D and Packialatha, A (2025) Campus 361 – AI-Integrated Education Management and Career Recommendation System. 2nd International Conference on Global Trends in Engineering and Technological Advancement (2nd ICGTETA’25), 2 . GOJAN School of Business and Technology, CHENNAI. ISBN 978-81-993196-8-4
2nd ICGTETA_25 Proceeding book.pdf
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Abstract
Our proposed web application provides a comprehensive online solution to streamline
academic, administrative, and communication activities in educational institutions. Developed
using Oracle APEX, it includes four customized login modules—Student, Parent, Educator,
and Admin—each designed for specific user needs.
The Student module offers personal profiles, fee management, transport details, service
requests, an online store, digital library, academic calendars, performance dashboards,
assignments, exam results, and feedback forms. An integrated AI chatbot assists with queries
and guidance. A key feature is the AI-Powered Career & Skill Recommendation System, which
analyzes students’ academic performance, interests, attendance, and extracurricular activities
to recommend suitable career paths, suggest skills to learn with links to free resources (NPTEL,
Coursera, edX), predict employability readiness via a skill gap dashboard, and connect students
to internships and job opportunities. An AI career counselor chatbot provides personalized
guidance, acting as a virtual mentor.
Educators can manage syllabi, assignments, and internal marks, while Parents monitor
academic progress. The Admin panel centralizes user management, service requests,
timetables, fee processing, and result uploads, ensuring efficiency and accountability. This
platform transforms education by integrating academic management with career guidance,
offering a secure, intelligent, and user-friendly system.
| Item Type: | Book |
|---|---|
| Subjects: | Computer Science Engineering > Computer Network |
| Domains: | Computer Science Engineering |
| Depositing User: | IR Admin |
| Date Deposited: | 07 Sep 2026 16:05 |
| Last Modified: | 08 Sep 2026 06:46 |
| URI: | https://ir.vistas.ac.in/id/eprint/22831 |
