Various technologies and applications such as cognitive computing, artificial intelligence, and learning analytics have received increased attention in recent years. The growing demand behind their adoption and exploitation in different application contexts has captured the attention of learning technology specialists, computer engineers, and business researchers who are attempting to decipher the phenomenon of personalized e-learning, its relation to already conducted research, and its implications for new research opportunities that effect innovations in teaching. Cognitive Computing in Technology-Enhanced Learning is a critical resource publication that aims to demonstrate state-of-the-art approaches of advanced data mining systems in e-learning, such as MOOCs and other innovative technologies, to improve learning analytics, as well as to show how new and advanced user interaction designs, educational models, and adoptive strategies can expand sustainability in applied learning technologies. Highlighting a range of topics such as augmented reality, ethics, and online learning environments, this book is ideal for educators, instructional designers, higher education faculty, school administrators, academicians, researchers, and students.

Online learning has become more and more common globally, whether for comfort, adapting to work hours or just having the freedom to study from anywhere. And now under the coronavirus pandemic, as people are having to stay at home, it has become more important than ever. Although the popularity of wireless network and portable smart device makes it possible for people to acquire and learn knowledge anytime and anywhere, it does not necessarily mean an increased learning performance. Relevant research in cognitive science has revealed possible limitations in online learning. For example, the knowledge acquired through online learning tends to be fragmented and lacks guidance for integrated thinking among different subjects, which makes it difficult for learners to form a systematic knowledge structure. Learners may experience cognitive overload, metacognitive illusion and low learning efficiency in self-regulated learning. It follows that, in the post COVID-19 era, online learning puts forward new requirements and challenges to the contemporary students, not only to their learning strategies but positive character traits in learning. Most of the current learning theories were developed in the early 20th century and may not fit in well with the current situation, then possibly leading to inefficient learning and increased learning burden. Therefore, it is necessary and important to reexplore the influencing factors and mechanisms that affect the learning efficiency of students at all levels nowadays, based on which we could construct a theoretical model of efficient learning model.

Digital Transformation in Higher Education is a pivotal reference through the transformative power of emerging technologies in academia. Addressing the dual nature of technology as both a challenge and an opportunity, this book presents a rich overview of strategies for integrating digital technology-driven advancements.

Active and Transformative Learning in STEAM Disciplines is a unique reference volume for the new student-centric and objectives-oriented learning environment where individual and team learning paths enhance problem solving capabilities.

The Evolution of Artificial Intelligence in Higher Education is a comprehensive guide to the transformative potential of AI in the higher education landscape, focused on the need to nurture technology literacy among educators and learners.

Learning Design refers to research and development work that equips teachers with tools and strategies to aid their design thinking. Its origin stems from two lines of inquiry: (i) how to represent teaching practice from a technical perspective in the development and delivery of online learning environments; and (ii) how to represent teaching practice in an appropriate form to enable teachers to share ideas about innovative online pedagogy and think about the process of design. The underlying premise of learning design is that, if effective, teaching and learning practice can be represented in a systematic way, thus supporting the process of reuse, which could ultimately lead to improved practice. A large international body of work has produced specifications of technical standards to support the delivery of online learning, different learning design representations to disseminate ‘best practice’ examples to support and encourage adaptation, and software tools and strategies to support the design process. This book presents a view of current thinking about learning design and provides insight into the future direction of this field of research and development. It is a timely contribution that will stimulate discussion about these issues and guide and advance the learning design field. This book was originally published as a special issue of Learning, Media and Technology.

This book presents thoughts and pathways to build revolutionary machine learning models with the new paradigm of machine learning to adapt behaviorism. It focuses on two aspects – one focuses on architecting a choice process to lead users on the certain choice path while the second focuses on developing machine learning models based on choice paradigm. This book is divided in three parts where part one deals with human choice and choice architecting models with stories of choice architects. Second part closely studies human choosing models and deliberates on developing machine learning models based on the human choice paradigm. Third part takes you further to look at machine learning based choice architecture. The proposed pioneering choice-based paradigm for machine learning presented in the book will help readers to develop products – help readers to solve problems in a more humanish way and to negotiate with uncertainty in a more graceful but in an objective way. It will help to create unprecedented value for business and society. Further, it will unveil a new paradigm for modern intelligent businesses to embark on the new journey; the journey of transition from shackled feature rich and choice poor systems to feature flexible and choice rich natural behaviors.

The ever evolving, technology-intensive nature of the twenty-first century workplace has caused an acceleration in the division of labour, whereby work practices are becoming highly specialised and learning and the communication of knowledge is in a constant state of flux. This poses a challenge for education and learning: as knowledge and expertise increasingly evolve, how can individuals be prepared through education to participate in specific industries and organisations, both as newcomers and throughout their careers? Learning Across Sites brings together a diverse range of contributions from leading international researchers to examine the impacts and roles which evolving digital technologies have on our navigation of education and professional work environments. Viewing learning as a socially organised activity, the contributors explore the evolution of learning technologies and knowledge acquisition in networked societies through empirical research in a range of industries and workplaces. The areas of study include public administration, engineering, production, and healthcare and the contributions address the following questions: How are learning activities organised? How are tools and infrastructures used? What competences are needed to participate in specialised activities? What counts as knowledge in multiple and diverse settings? Where can parallels be drawn between workplaces? Addressing an emerging problem of adaptation in contemporary education, this book is essential reading for all those undertaking postgraduate study and research in the fields of educational psychology, informatics and applied information technology.

The experts and practitioners contributing to this volume reveal a complex reality of HEI today. The book links the debate on education to topical issues in politics, society and economy, including questions of technological progress, social responsibility, sustainability, well-being and, broadly understood, resilience.

Essays in Group-Cognitive Science, intros to CSCL research, methodology and findings. Vol 10 of Gerry Stahl's assembled texts.