Affective Learning In Digital Education

While online learning was an existing practice, the COVID-19 pandemic greatly accelerated its capabilities and forced educational organizations to swiftly introduce online learning for all units. Though schools will not always be faced with forced online learning, it is apparent that there are clear advantages and disadvantages to this teaching method, with its usage in the future cemented. As such, it is imperative that methods for measuring and assessing the effectiveness of online and blended learning are examined in order to improve outcomes and future practices. Measurement Methodologies to Assess the Effectiveness of Global Online Learning aims to assess the effectiveness of online teaching and learning in normal and pandemic situations by addressing challenges and opportunities of adoption of online platforms as well as effective learning strategies, investigating the best pedagogical practices in digital learning, questioning how to improve student motivation and performance, and managing and measuring academic workloads online. Covering a wide range of topics such as the future of education and digital literacy, it is ideal for teachers, instructional designers, curriculum developers, educational software developers, academics, researchers, and students.

"This book focuses on the study and application of human computer interaction principles in the design of online education"--Provided by publisher.

This book constitutes the thoroughly refereed proceedings of the First International Conference on Brain Function Assessment in Learning, BFAL 2017, held in Patras, Greece, in September 2017. The 16 revised full papers presented together with 2 invited talks and 6 posters were carefully selected from 28 submissions. The BFAL conference aims to regroup research in multidisciplinary domains such as neuroscience, health, computer science, artificial intelligence, human-computer interaction, education and social interaction on the theme of Brain Function Assessment in Learning.

Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.

'Affective Learning Together' contains in-depth theoretical reviews and case studies in the classroom, of the social and affective dimensions of group learning in a variety of educational situations and taught disciplines, from small groups working on design projects or debating topics in biology and in history in schools.

How to utilize digital technology to engage learners in deep learning is an issue that warrants significant attention in 21st century education. Deep learning refers to learners engagement in critical and creative thinking, making inferences and transferring knowledge. Modern technologies like virtual reality, artificial intelligence, and 3D visualization provide the platform for deep learning in an educational setting more effectively. This book presents a collection of essays on the relationship between digital technologies and deep learning. The edited volume focuses on cognitive, metacognitive and affective processes in digital technology-based deep learning. A unique feature of the book is its emphasis on bridging the theories with practice where the practice of deep learning with digital technology is well-grounded in relevant theories and theoretical frameworks. Moreover, the book includes case studies to effectively promote the application of digital technology in deep learning. As such, the book is rightly poised to address current issues facing deep learning and digital technology in education. The audience will find this book a useful companion as they will soon discover that this book provides helpful information on both theoretical and practical aspects in deep learning with digital technology. It also serves as an excellent resource for researchers and individual professionals who seek to understand the relationship between deep learning and digital technology in education.