Full Description
E-learning has become an important part of our educational life with the development of e-learning systems and platforms and the need for online and remote learning. ICT and computational intelligence techniques are being used to design more intelligent and adaptive systems. However, the art of designing good real-time e-learning systems is difficult as different aspects of learning need to be considered including challenges such as learning rates, involvement, knowledge, qualifications, as well as networking and security issues. The earlier concepts of standalone integrated virtual e-learning systems have been greatly enhanced with emerging technologies such as cloud computing, mobile computing, big data, Internet of Things (IoT), AI and machine learning, and AR/VT technologies.
With this book, the editors and authors wish to help researchers, scholars, professionals, lecturers, instructors, developers, and designers understand the fundamental concepts, challenges, methodologies and technologies for the design of performant and reliable intelligent and adaptive real time e-learning systems and platforms. This edited volume covers state of the art topics including user modeling for e-learning systems and cloud, IOT, and mobile-based frameworks. It also considers security challenges and ethical conduct using Blockchain technology.
Contents
Part I: Introduction and pedagogies of e-learning systems with intelligent techniques
Chapter 1: Introduction
Chapter 2: Goal-oriented adaptive e-learning
Chapter 3: Predicting students' behavioural engagement in microlearning using learning analytics model
Chapter 4: Student performance prediction for adaptive e-learning systems
Part II: Technologies in e-learning
Chapter 5: AI in e-learning
Chapter 6: Mobile learning as the future of e-learning
Chapter 7: Smart e-learning transition using big data: perspectives and opportunities
Chapter 8: E-learning using big data and cloud computing
Chapter 9: E-learning through virtual laboratory environment: developing of IoT workshop course based on Node-RED
Chapter 10: Mnemonics in e-learning using augmented reality
Chapter 11: E-learning tools and smart campus: boon or bane during COVID-19
Part III: Case studies
Chapter 12: Bioinformatics algorithms: course, teaching pedagogy and assessment
Chapter 13: Active learning in E-learning: a case study to teach elliptic curve cryptosystem, its fast computational algorithms and authentication protocols for resource constraint RFID-sensor integrated mobile devices
Chapter 14: Conclusion
