Scalable Online Education Platforms in Higher Education for Enhancing Students Academic Performance

Abstract

Using online education platforms, which provide accessible, personalized and highly customizable learning experiences, can greatly increase students’ engagement and performance in the classroom. These scalable computing systems-based platforms have tools that enable them to choose their pace of learning, access various content, and communicate in multiple ways. Some of the talking points include problems with socializing, differences in self-control among students, and digital divide challenges. A Scalable E-Learning Platforms for Educational Social Networking (E-LP-ESN) is a way to integrate social networking features into online learning environments to address these issues. This approach aims to make the classroom a pleasant and engaging place for students. The way to achieve this goal is to have student-centered instructional strategies that focus on their interpersonal development. Third parties and their discussion forums, real-time collaboration tools, and information provided by third parties are too important aspects of the E-LP-ESN programs not to mention. Recent advances in Machine Learning (ML) have further enhanced the E-LP-ESN approach through the use of Artificial Intelligence (AI) image and video. Using advanced multimedia tools, this technology makes it easy to manipulate and analyze large scales of visual input to improve student experience. The results of the simulated experiments show that E-LP-ESN with the combination of AI and ML significantly outperforms traditional online learning systems in terms of student engagement, performance and in satisfaction. When combined with these technologies, factors that make learning fun, effective and enjoyable, E-learning can be revolutionary.