Enhancing Industry-Academia Collaboration Through an Automated Smart Internship and Evaluation System
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Abstract
In the current educational ecosystem, internships and industrial training play a crucial role in preparing students for real-world challenges. However, the traditional internship management process is often fragmented, manual, and lacks proper monitoring and evaluation mechanisms. Students face difficulties in finding suitable opportunities, while institutions struggle to track performance and ensure meaningful industry engagement.
This research proposes a Smart Internship and Evaluation System (SIES), a web-based platform designed to automate and streamline the entire internship lifecycle.It enables students to search and apply for internships, allows companies to manage candidates and assign tasks, and provides institutions with real-time monitoring and evaluation tools.
The system incorporates features such as centralized dashboards, real-time application tracking, task management, performance evaluation, and placement opportunities based on student performance. Built using modern technologies like React.js, Node.js, and MongoDB, the platform ensures scalability, security, and efficiency. The proposed system enhances transparency, reduces administrative workload, and strengthens industry-academia collaboration, ultimately improving student employability outcomes
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