This book focuses on the interplay between pedagogy and technology, and their fusion for the advancement of smart learning environments. It discusses various components of this interplay, including learning and assessment paradigms, social factors and policies, emerging technologies, innovative application of mature technologies, transformation of curriculum and teaching behavior, transformation of administration, best infusion practices, and piloting of new ideas. The book provides an archival forum for researchers, academics, practitioners and industry professionals interested and/or engaged in reforming teaching and learning methods by promoting smart learning environments. It also facilitates discussions and constructive dialogue among various stakeholders on the limitations of existing learning environments, the need for reform, innovative uses of emerging pedagogical approaches and technologies, and sharing and promoting best practices, leading to the evolution, design and implementation of smart learning environments.

This book constitutes the refereed proceedings of the 13th International Conference on Blended Learning, ICBL 2020, held in Bangkok, in August 2020. The 33 papers presented were carefully reviewed and selected from 70 submissions. The conference theme of ICBL 2020 is Blended Learning : Education in a Smart Learning Environment. The papers are organized in topical sections named: Blended Learning, Hybrid Learning, Online Learning, Enriched and Smart Learning, Learning Management System and Content and Instructional Design.

Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning

This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2021), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from April 10 to 11, 2021. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

The two-volume set, LNCS 13325 and 13326, are conference proceedings that constitutes the refereed proceedings of the 10th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2022, held as part of the 24th International Conference, HCI International 2022, which took place during June-July 2022. The conference was held virtually due to the COVID-19 pandemic. The 58 papers of DAPI 2022 are organized in topical sections named for each volume: Part I: User Experience and Interaction Design for Smart Ecosystems; Smart Cities, Smart Islands, and Intelligent Urban Living; Smart Artifacts in Smart Environments; and Opportunities and Challenges for the Near Future Smart Environments Part II: Smart Living in Pervasive IoT Ecosystems; Distributed, Ambient, and Pervasive Education and Learning; Distributed, Ambient, and Pervasive Well-being and Healthcare; and Smart Creativity and Art.

This book introduces readers to the current status of smart learning in China by providing extensive and accurate data from different contexts of smart learning. In particular, it investigates smart learning in smart cities, which extends the concept of smart learning to cover both formal and informal learning, and to support life-long learning. With digital technologies and the Internet becoming increasingly integrated into learning, the demand for smart learning has grown steadily, especially in smart city scenarios. As the need for life-long learning is on the rise, smart learning environments in cities should be equipped to meet people’s demands. Smart learning/education is also one of the key applications of smart cities. Though the book’s content mainly focuses on the educational technology field, research in cities and industries is also included. This book offers a valuable resource for graduate students in educational technology, smart learning environment and smart city researchers, cooperative university managers, and all others who are interested in smart learning industries.

This three-volume set constitues selected papers presented during the 17th International Conference on Computer Science and Education, ICCSE 2022, held in Ningbo, China, in August 2022. The 168 full papers and 43 short papers presented were thoroughly reviewed and selected from the 510 submissions. They focus on a wide range of computer science topics, especially AI, data science, and engineering, and technology-based education, by addressing frontier technical and business issues essential to the applications of data science in both higher education and advancing e-Society.

This book focuses on all the technologies involved in improving the teaching and learning process of some of the sensor-based IoT topics, such as virtual sensors, simulated data acquisition, virtual and remote labs for IoT sensing, gamification experiences and innovative teaching materials, among others. In particular, the articles inside the book show excellent works about hot topics, such as: - Remote labs for IoT teaching, including the full development cycle. - Practical guides for IoT cybersecurity. - Innovative multimodal learning analytics architecture that builds on software-defined networks and network function virtualization principles. - Problem-based learning experiences using designed complex sensor-based IoT ecosystems with sensors, actuators, microcontrollers, plants, soils and irrigation systems. - Block-based programming extensions to facilitate the creation of mobile apps for smart learning experiences. The articles published in this book present only some of the most important topics about sensor-based IoT learning and teaching. However, the selected papers offer significant studies and promising environments.

The advent of connected, smart technologies for the built environment may promise a significant value that has to be reached to develop digital city models. At the international level, the role of digital twin is strictly related to massive amounts of data that need to be processed, which proposes several challenges in terms of digital technologies capability, computing, interoperability, simulation, calibration, and representation. In these terms, the development of 3D parametric models as digital twins to evaluate energy assessment of private and public buildings is considered one of the main challenges of the last years. The ability to gather, manage, and communicate contents related to energy saving in buildings for the development of smart cities must be considered a specificity in the age of connection to increase citizen awareness of these fields. The Handbook of Research on Developing Smart Cities Based on Digital Twins contains in-depth research focused on the description of methods, processes, and tools that can be adopted to achieve smart city goals. The book presents a valid medium for disseminating innovative data management methods related to smart city topics. While highlighting topics such as data visualization, a web-based ICT platform, and data-sharing methods, this book is ideally intended for researchers in the building industry, energy, and computer science fields; public administrators; building managers; and energy professionals along with practitioners, stakeholders, researchers, academicians, and students interested in the implementation of smart technologies for the built environment.