Introduction

This book discusses the newest approach to online learning systems in higher education. As e-Learning platforms change their mechanisms for data processing and storage, there is a need to move these systems toward being more efficient and smarter. This book covers online learning systems and their application to large-scale data along with the technological aspects of these processes and problem-solving methods.

Content Overview

Online Learning Systems: Methods and Applications with Large-Scale Data discusses the efficiency measurement and environmental impact of online education. The book offers a parametric evaluation and categorization of online learning systems and provides an exploration of big data ecosystems in cloud computing. Descriptive analytical methods that assist in finding solutions for big data challenges are also covered within the book.

Intended Audience

The book is written for academicians, which includes teachers, students, and higher education policymakers who believe in transforming the education industry, as well as research scholars and those working in education technology and artificial intelligence. Industry professionals involved in education management and those working in e-Learning companies will also find this book useful.