Microservices-Based Architecture for an AI-Driven Social Listening System Supporting Internship Preparation

Abstract

Internships in education are a necessary step between education and work life, but students face difficulties when making this transition. The paper describes i-listening, an intelligent listening social application created to improve pre-internship preparation. Through cutting-edge Artificial Intelligence techniques, such as Natural Language Processing, machine learning, and predictive analytics, the platform helps students to get actionable feedback about the workplace culture, industry trends, and employer expectations. This allows acquisition of practical and industry-based skills and competencies that can be helpful in the successful internship experiences. The paper identifies two key contributions in the study, namely the development and deployment of the i-listening application using advanced IT architecture, and its capacity to support recruits (management and IT students) into the workplace with less resistance. The results indicate that it is an AI-based paradigm of transformative pre-internship education.