A Novel Cloud-based Framework to Predict the Employability of Students

Abstract

Predicting students’ employability during graduation is a crucial task that can significantly impact their future careers. This research proposed a novel cloud-based framework to address this problem. The framework combines multiple data sources and machine learning algorithms to predict student employability comprehensively. The results of the performance evaluation showed that the framework performed well. This framework provides a valuable tool for universities, employers, and students, as it provides insights into students’ employability and helps them make informed decisions about their future careers. By leveraging the latest advances in cloud computing, sustainable education, disruptive technologies, machine learning, and artificial intelligence, the proposed framework provides a valuable tool for universities, employers, and students, contributing to the sustainable development of students and the workforce. This research’s results demonstrate the proposed framework’s potential and provide a foundation for future research.