Nexora – Next Gen Navigator: An AI-Powered Personalized Educational and Career Guidance Platform
Students frequently make educational and career decisions while facing fragmented information about academic pathways, occupations, courses, scholarships, certifications and entry-level opportunities. Generic guidance may not adequately reflect an individual learner’s academic background, current skills, interests, goals, financial constraints or preferred location. This paper presents Nexora – Next Gen Navigator, a proposed AI-powered web application intended to provide personalized educational and career guidance through a unified platform. The system is designed to collect a student profile, interpret academic and skill-related information, and generate context-aware suggestions for career paths, colleges, courses, scholarships, certifications, internships and skill-development opportunities. Its planned capabilities include skill-gap analysis, personalized learning and career roadmaps, resume-building assistance and progress tracking. The proposed implementation uses React.js for the frontend, Node.js and Express.js for backend services, MongoDB for persistent data storage, and an external generative AI service such as the OpenAI API or Google Gemini API for conversational and recommendation support. The paper describes the problem context, related research, proposed system, architecture, recommendation workflow, implementation plan and a functional evaluation strategy. As the application has not yet been deployed and evaluated, the paper does not claim measured recommendation accuracy, improved placement rates or validated user benefits. Instead, it defines test scenarios and evaluation criteria that can be applied when the application is implemented and tested. Nexora is intended to support informed decision-making while keeping final educational and career choices with the student.
Authors
- M. Suchitra
- P. Srinivas
- N. Ekta
- N. Nikhil
- Dharmendar Roy
Publication Details
- Journal
- Iconic Research and Engineering Journals
- Published
- 2026-11-06
- DOI
- https://doi.org/10.64388/ire1724878
- Primary Topic
- Edcuational Technology Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00