Analytics-led digital internship management platform for industry-university collaboration

Abstract

Internship training is a key tool in bridging theoretical knowledge and the industry applications and expectations. While commercially available job matching platforms serve the needs of employment seekers and job providers, a paucity is seen in facilitating a similar need for internship training. Anchored on the Learning Analytics Framework, the proposed research application, referred to hereafter as InternNexus, aims to provide a practical model of a digital internship management platform for analytics-based decision making by transforming the internship experience into a structured, transparent, and efficient process. By being into action research, the proposed prototype in this study suggests creating profiles demonstrating applicants’ academic background and other qualifications, allowing them to match their interests to training opportunities, track applications in real-time, and receive personalized recommendations. Meanwhile, the employers post the internship vacancies, manage candidates, and make offers directly through the platform, while the university administration can verify internship status, monitor student progress, and review the entire process of the internship. The technological architecture used in this research are ReactJS for a responsive frontend interface, NodeJS, and ExpressJS for a scalable backend framework supported by MongoDB's flexible document-oriented database technologies. Due to its exceptional performance in handling real-time data exchanges, MongoDB was selected to support cross-platform compatibility that is essential for connecting diverse stakeholders. The users of this system are students who seek internship opportunities, companies looking for trainees, and the educational institutes monitoring and analyzing student performance during their industrial training. Theoretically, the research advances the Learning Analytics Framework to the action research domain, and its practical contribution can be extended beyond the immediate implementation to a government-sponsored centralized platform to streamline industrial training of students, especially at the university level, to accelerate the timely completion of degree programs and to produce well-trained graduates. This action research opens the possibilities of widening theoretical models for immediate value-generating software development projects for the education sector to yield the paybacks of action research in computing.