Online Skill Assessment Using AI

Abstract

The increasing demand for efficient and insightful skill evaluation in recruitment and education necessitates a move beyond traditional, manual assessment methods. This project details the design and development. A sophisticated AI-driven online skill assessment platform. Built with a modern, robust tech stack—Next.js for server-side rendering and API routes, TypeScript to ensure code reliability and maintainability, Tailwind CSS for a utility-first and responsive user interface, and MongoDB as the flexible NoSQL database—the platform intelligently automates the entire assessment lifecycle. The platform uses artificial intelligence to generate questions tailored to specific subjects and contexts, and to evaluate both descriptive and programming responses. Instead of relying on keyword matching, it examines logical flow, structural accuracy, and conceptual understanding, providing candidates with clear and actionable feedback. The project was successfully deployed and tested, demonstrating its ability to reduce administrative overhead, eliminate grading bias, and deliver a highly detailed, personalized assessment experience. Skill AI serves as a proof of concept for integrating artificial intelligence into full stack web applications, enabling more adaptive, fair, and intelligent educational technology solutions.

Introduction

Rapid digital transformation has increased the demand for job-ready skills, exposing a gap between traditional education and industry expectations. Although EdTech platforms have expanded rapidly, most focus either on content delivery or assessment, lacking integrated AI-driven evaluation and personalized learning. Despite the growing e-learning market, current platforms such as Coursera, Udemy, and HackerRank do not provide a complete ecosystem combining skill assessment, customized learning paths, credential verification, and career support.

The proposed system addresses this gap by integrating AI-powered assessment and personalized learning into a single platform. Using advanced AI technologies, including natural language processing and adaptive algorithms, the system analyzes learner performance, identifies skill gaps, generates intelligent tests, and recommends tailored learning content. A comprehensive literature review of research papers, platforms, and market trends supports the need for such an end-to-end solution.

The platform includes two main modules: an Admin module for analytics, student management, content control, certificate approval, and resume evaluation; and a Student module offering AI-based tests, personalized learning paths, progress tracking, leaderboards, certificate requests, and an AI-powered resume builder. The system is built using modern web technologies such as Next.js, TypeScript, Tailwind CSS, MongoDB, and Google Gemini API, with secure authentication and real-time communication.

Implemented using the Scrum methodology and an API-first architecture, the system aims to deliver a scalable, secure, and intelligent learning environment. Overall, the project proposes a smart, integrated EdTech platform that bridges the skill gap by combining assessment, learning, and career readiness through AI-driven personalization and analytics.

Conclusion

SkillAI demonstrates the powerful synergy between artificial intelligence and educational technology, creating a unified environment for skill evaluation and learning. With the integration of Google’s Gemini API, the platform delivers adaptive test generation, personalized learning recommendations, and automated assessments, successfully addressing the limitations present in existing educational systems. The system’s modular architecture, with separate admin and student modules enhanced by AI capabilities, offers a scalable and maintainable solution that adapts to evolving educational needs. The integration of live features such as chat and instant assessment feedback strengthens user engagement and enables seamless communication among stakeholders. Notable achievements include the creation of an intelligent assessment engine that generates questions tailored to context, the development of a dynamic learning management system that adapts to individual learner performance, and the implementation of an automated certification mechanism that upholds the credibility of issued credentials. Furthermore, the platform’s responsive design and compatibility across devices make high quality education accessible to a broad and diverse audience. While the project successfully fulfills its main objectives, potential advancements may include the creation of a mobile application, the use of blockchain for secure credential verification, the application of machine learning to deliver advanced analytics, and integration with professional job portals. These upgrades would strengthen the platform’s foundation, establishing it as an innovative AI powered solution with the ability to transform how skills are assessed, developed, and validated in the modern digital landscape. The positive user feedback and performance metrics validate the project\'s success in creating a valuable educational tool that benefits students, educators, and employers alike. SkillAI represents a significant step toward personalized, accessible, and credible digital education that aligns with the evolving needs of the modern workforce and learning landscape.

References

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Copyright

Copyright © 2026 Kalpesh Laxman Mhatre, Aryan Avinash Gulve, Adil Nawaz Abdul Alim Sharif, Professor Mr. Sanjay N. Jadhav. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.