INTERNLY: A MOBILE PLATFORM FOR CONNECTING NIGERIAN STUDENTS TO INTERNSHIP OPPORTUNITIES

• A. A. Akinlabi

  Department of Computer Engineering, School of Electrical Systems Engineering, Federal University of Technology, Akure, Ondo State, Nigeria

• A. P. Faluyi

  Department of Computer Engineering, School of Electrical Systems Engineering, Federal University of Technology, Akure, Ondo State, Nigeria

• J. M. Iberedem

  Department of Computer Engineering, School of Electrical Systems Engineering, Federal University of Technology, Akure, Ondo State, Nigeria

• F. M. Dahunsi

  Department of Computer Engineering, School of Electrical Systems Engineering, Federal University of Technology, Akure, Ondo State, Nigeria

Finding the right internships remains a significant challenge for undergraduate students in Nigeria due to the lack of effective filtering and matching mechanisms on existing platforms like job boards, LinkedIn, and Indeed. These platforms do not take into consideration factors such as skill competency, experience or alignment with professional goals because they rely on simple keyword searches or manual filters including location and job title. INTERNLY is a mobile platform that bridges the gap between students seeking internships and organizations offering these opportunities. The platform’s front-end component was built using React Native, while Node.js, Express, and MongoDB served as the back-end technologies. Cloudinary, a cloud media storage managed image and video uploads. INTERNLY utilizes rule-based matching algorithms and centralized management tools to streamline the placement process. Prospective Interns are matched to internship opportunities using a scoring system that prioritizes their skills and interests and employer requirements like minimum Cumulative Grade Point Average (CGPA), skills or experience. Students can create profiles, browse tailored internship listings and apply for relevant roles, while organizations can register, post openings and manage applications efficiently. A structured database supports user information storage, and filtering algorithms generate personalized recommendations. Security measures that were put in place include encrypted authentication and data protection. Initial testing of the INTERNLY prototype demonstrates improved efficiency in internship placement. The platform reduces the time and effort required by all stakeholders, increasing accessibility and engagement.

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