"This book goes beyond traditional discussion on technology enhanced learning provides research and insights on increasing the efficiency of learning for individuals and groups, facilitating the transfer and sharing of knowledge in organizations, and understanding of the learning process by exploring links among human learning, cognition, and technologies. "--Provided by publisher.

The use of technology in learning has increased dramatically. Training and education is now utilizing and almost integrated with the World Wide Web, podcasts, mobile and distant learning, interactive videos, serious games, and a whole range of e-learning. However, has such technology enhanced learning been effective? And how can it better serve training and education?E-learning must be 'brain friendly', so it optimizes learning to the cognitive architecture of the learners. If technology enhanced learning promotes the formation of effective mental representations and works with the human cognitive system, then the learners will not only be able to acquire information more efficiently, but they will also remember it better and use it. Technology should not be the driving force in shaping e-learning, but rather how that technology can better serve the cognitive system. This volume, originally published as a special issue of Pragmatics & Cognition 16:2 (2008) and partly in Pragmatics & Cognition 17:1 (2009), explores the research frontiers in cognition and learning technology. It provides important theoretical insights into these issues, as well as very practical implications of how to make e-learning more brain friendly and effective.

Self-regulated learning (SRL) subsumes key aspects of the learning process, such as cognitive strategies, metacognition and motivation, in one coherent construct. Central to this construct are the autonomy and responsibility of students to take charge of their own learning. Skills for self-regulation can be encouraged both directly and indirectly through a range of learning activities. In this book we look specifically at the ways in which technology enhanced learning environments (TELEs) have been used to support self-regulation. The book provides an overview of recent studies on SRL in TELEs in Europe – a perspective which is new and has not been articulated hitherto. It addresses conceptual and methodological questions as well as practices in technology enhanced learning. While the focus is on European studies, we are aware that much of the groundwork in the field of SRL has emanated from the United States. The book is divided into three parts: (A) Foundations of SRL in TELEs, (B) Empirical studies on SRL in TELEs and (C) SRL in TELEs: perspectives on future developments. The book presents a rich resource of information for researchers and educators at all levels who are interested in supporting the acquisition of SRL through TELEs.

Multiple intelligences (MI) as a cognitive psychology theory has significantly influenced learning and teaching. Research has demonstrated a strong association between individual intelligences and their cognitive processes and behaviors. However, it remains unknown how each of or a combination of these intelligences can be effectively optimized through instructional intervention, particularly through the use of emerging learning technology. On the other hand, while efforts have been made to unveil the relationship between information and communication technology (ICT) and individual learner performance, there is a lack of knowledge in how MI theory may guide the use of ICTs to enhance learning opportunities for students. Examining Multiple Intelligences and Digital Technologies for Enhanced Learning Opportunities is an essential reference book that generates new knowledge about how ICTs can be utilized to promote MI in various formal and informal learning settings. Featuring a range of topics such as augmented reality, learning analytics, and mobile learning, this book is ideal for teachers, instructional designers, curriculum developers, ICT specialists, educational professionals, administrators, instructors, academicians, and researchers.

This open access book contains observations, outlines, and analyses of educational robotics methodologies and activities, and developments in the field of educational robotics emerging from the findings presented at FabLearn Italy 2019, the international conference that brought together researchers, teachers, educators and practitioners to discuss the principles of Making and educational robotics in formal, non-formal and informal education. The editors’ analysis of these extended versions of papers presented at FabLearn Italy 2019 highlight the latest findings on learning models based on Making and educational robotics. The authors investigate how innovative educational tools and methodologies can support a novel, more effective and more inclusive learner-centered approach to education. The following key topics are the focus of discussion: Makerspaces and Fab Labs in schools, a maker approach to teaching and learning; laboratory teaching and the maker approach, models, methods and instruments; curricular and non-curricular robotics in formal, non-formal and informal education; social and assistive robotics in education; the effect of innovative spaces and learning environments on the innovation of teaching, good practices and pilot projects.

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.

Education is a hot topic. From the stage of presidential debates to tonight's dinner table, it is an issue that most Americans are deeply concerned about. While there are many strategies for improving the educational process, we need a way to find out what works and what doesn't work as well. Educational assessment seeks to determine just how well students are learning and is an integral part of our quest for improved education. The nation is pinning greater expectations on educational assessment than ever before. We look to these assessment tools when documenting whether students and institutions are truly meeting education goals. But we must stop and ask a crucial question: What kind of assessment is most effective? At a time when traditional testing is subject to increasing criticism, research suggests that new, exciting approaches to assessment may be on the horizon. Advances in the sciences of how people learn and how to measure such learning offer the hope of developing new kinds of assessments-assessments that help students succeed in school by making as clear as possible the nature of their accomplishments and the progress of their learning. Knowing What Students Know essentially explains how expanding knowledge in the scientific fields of human learning and educational measurement can form the foundations of an improved approach to assessment. These advances suggest ways that the targets of assessment-what students know and how well they know it-as well as the methods used to make inferences about student learning can be made more valid and instructionally useful. Principles for designing and using these new kinds of assessments are presented, and examples are used to illustrate the principles. Implications for policy, practice, and research are also explored. With the promise of a productive research-based approach to assessment of student learning, Knowing What Students Know will be important to education administrators, assessment designers, teachers and teacher educators, and education advocates.