This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators' and learners' data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: * Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; * Using learning analytics to predict student performance; * Using learning analytics to create learning materials and educational courses; and * Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

This book examines the conflicts arising from the implementation of privacy principles enshrined in the GDPR, and most particularly of the ``Right to be Forgotten'', on a wide range of contemporary organizational processes, business practices, and emerging computing platforms and decentralized technologies. Among others, we study two ground-breaking innovations of our distributed era: the ubiquitous mobile computing and the decentralized p2p networks such as the blockchain and the IPFS, and we explore their risks to privacy in relation to the principles stipulated by the GDPR. In that context, we identify major inconsistencies between these state-of-the-art technologies with the GDPR and we propose efficient solutions to mitigate their conflicts while safeguarding the privacy and data protection rights. Last but not least, we analyse the security and privacy challenges arising from the COVID-19 pandemic during which digital technologies are extensively utilized to surveil people's lives.

This book examines the conflicts arising from the implementation of privacy principles enshrined in the GDPR, and most particularly of the ``Right to be Forgotten'', on a wide range of contemporary organizational processes, business practices, and emerging computing platforms and decentralized technologies. Among others, we study two ground-breaking innovations of our distributed era: the ubiquitous mobile computing and the decentralized p2p networks such as the blockchain and the IPFS, and we explore their risks to privacy in relation to the principles stipulated by the GDPR. In that context, we identify major inconsistencies between these state-of-the-art technologies with the GDPR and we propose efficient solutions to mitigate their conflicts while safeguarding the privacy and data protection rights. Last but not least, we analyse the security and privacy challenges arising from the COVID-19 pandemic during which digital technologies are extensively utilized to surveil people's lives.