Active Learning for Digital Transformation in Healthcare Education, Training and Research discusses the potential of advanced training of health professionals as a contributing factor to improve treatment outcomes. By reading this book, professionals who deal with patients with low health literacy will be prepared to promote better access to digital tools, understand the habits of users of health services, and empower engagement. The book contains a set of techniques and instruments associated with health literacy, communication skills and personal development that will enable their application in good daily practices and assist healthcare professionals to promote digital transformation to patients. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about how they can be an effective agent of change in healthcare. - Discusses the potential of patient education through the training of health professionals to improve patient engagement and adherence to treatment - Presents techniques from real-world examples to demonstrate the efficacy of better communication between health professionals and patients, especially in the digital medicine era - Outlines digital tools that can be used to strengthen the healthcare professional-patient relationship

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.

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.

Technology-Enhanced Healthcare Education promotes the best practices and lessons learnt from COVID-19 and highlights the importance and impact of using information systems to increase levels of health literacy.

This open access volume provides insight into how organizations change through the adoption of digital technologies. Opportunities and challenges for individuals as well as the organization are addressed. It features four major themes: 1. Current research exploring the theoretical underpinnings of digital transformation of organizations. 2. Insights into available digital technologies as well as organizational requirements for technology adoption. 3. Issues and challenges for designing and implementing digital transformation in learning organizations. 4. Case studies, empirical research findings, and examples from organizations which successfully adopted digital workplace learning.

This book focuses on selected best practices for effective active learning in Higher Education. Contributors present the epistemology of active learning along with specific case studies from different disciplines and countries. Discussing issues around ICTs, collaborative learning, experiential learning and other active learning strategies.

Emotional intelligence has emerged as an important area of research in the artificial intelligence field as it covers a wide range of real-life domains. Though machines may never need all the emotional skills that people need, there is evidence to suggest that machines require at least some of these skills to appear intelligent when interacting with people. To understand how deep learning-based emotional intelligence can be applied and utilized across industries, further study on its opportunities and future directions is required. Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence explores artificial intelligence applications, such as machine and deep learning, in emotional intelligence and examines their use towards attaining emotional intelligence acceleration and augmentation. It provides research on tools used to simplify and streamline the formation of deep learning for system architects and designers. Covering topics such as data analytics, deep learning, knowledge management, and virtual emotional intelligence, this reference work is ideal for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.