This book constitutes the proceedings of the 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, held in Delft, The Netherlands, in September 2019. The 41 research papers and 50 demo and poster papers presented in this volume were carefully reviewed and selected from 149 submissions. The contributions reflect the debate around the role of and challenges for cutting-edge 21st century meaningful technologies and advances such as artificial intelligence and robots, augmented reality and ubiquitous computing technologies and at the same time connecting them to different pedagogical approaches, types of learning settings, and application domains that can benefit from such technologies.
This volume brings together internationally known researchers representing different theoretical perspectives on students' self-regulation of learning. Diverse theories on how students become self-regulated learners are compared in terms of their conceptual origins, scientific form, research productivity, and pedagogical effectiveness. This is the only comprehensive comparison of diverse classical theories of self-regulated learning in print. The first edition of this text, published in 1989, presented descriptions of such differing perspectives as operant, phenomenological, social learning, volitional, Vygotskian, and constructivist theories. In this new edition, the same prominent editors and authors reassess these classic models in light of a decade of very productive research. In addition, an information processing perspective is included, reflecting its growing prominence. Self-regulation models have proven especially appealing to teachers, coaches, and tutors looking for specific recommendations regarding how students activate, alter, and sustain their learning practices. Techniques for enhancing these processes have been studied with considerable success in tutoring sessions, computer learning programs, coaching sessions, and self-directed practice sessions. The results of these applications are discussed in this new edition. The introductory chapter presents a historical overview of research and a theoretical framework for comparing and contrasting the theories described in the following chapters, all of which follow a common organizational format. This parallel format enables the book to function like an authored textbook rather than a typical edited volume. The final chapter offers an historical assessment of changes in theory and trends for future research. This volume is especially relevant for students and professionals in educational psychology, school psychology, guidance and counseling, developmental psychology, child and family development, as well as for students in general teacher education.
Students who self-regulate are more likely to improve their academic performance, find value in their learning process, and continue to be effective lifelong learners. However, online students often struggle to self-regulate, which may contribute to lower academic performance. Likewise, less experienced online teachers who are in the process of implementing-or have implemented-a shift from in-person to distance learning may struggle to enable their students to employ effective self-regulation techniques. Supporting Self-Regulated Learning and Student Success in Online Courses examines current theoretical frameworks, research projects, and empirical studies related to the design, implementation, and evaluation of self-regulated learning models and interventions in online courses and discusses their implications. Covering key topics such as online course design, student retention, and learning support, this reference work is ideal for administrators, policymakers, researchers, academicians, practitioners, scholars, instructors, and students.
Students who self-regulate are more likely to improve their academic performance, find value in their learning process, and continue to be effective lifelong learners. However, online students often struggle to self-regulate, which may contribute to lower academic performance. Likewise, less experienced online teachers who are in the process of implementing—or have implemented—a shift from in-person to distance learning may struggle to enable their students to employ effective self-regulation techniques. Supporting Self-Regulated Learning and Student Success in Online Courses examines current theoretical frameworks, research projects, and empirical studies related to the design, implementation, and evaluation of self-regulated learning models and interventions in online courses and discusses their implications. Covering key topics such as online course design, student retention, and learning support, this reference work is ideal for administrators, policymakers, researchers, academicians, practitioners, scholars, instructors, and students.
This book presents the outcomes of four years of educational research in the EU-supported project called ROLE (Responsive Online Learning Environments). ROLE technology is centered around the concept of self-regulated learning that creates responsible learners, who are capable of critical thinking and able to plan their own learning processes. ROLE allows learners to independently search for appropriate learning resources and then reflect on their own learning process and progress. To accomplish this, ROLE ́s main objective is to support the development of open personal learning environments (PLE's). ROLE provides a framework consisting of “enabler spaces” on the one hand and tools, content, and services on the other. Utilizing this framework, learners are invited to create their own controlled and preferred learning environments to trigger and motivate self-regulated learning. Authors of this book are researchers, developers and teachers who have worked in the ROLE project and belong to the ROLE partner consortium consisting of 16 internationally renowned research institutions, including those from 6 EU countries and China. Chapters include numerous practical tutorials to guide the reader in creating innovative and useful learning widgets and present the best practices for the development of PLE's.
Online learning has increasingly been viewed as a possible way to remove barriers associated with traditional face-to-face teaching, such as overcrowded classrooms and shortage of certified teachers. While online learning has been recognized as a possible approach to deliver more desirable learning outcomes, close to half of online students drop out as a result of student-related, course-related, and out-of-school-related factors (e.g., poor self-regulation; ineffective teacher-student, student-student, and platform-student interactions; low household income). Many educators have expressed concern over students who unexpectedly begin to struggle and appear to fall off track without apparent reason. A well-implemented early warning system, therefore, can help educators identify students at risk of dropping out and assign and monitor interventions to keep them on track for graduation. Despite the popularity of early warning systems, research on their design and implementation is sparse. Early Warning Systems and Targeted Interventions for Student Success in Online Courses is a cutting-edge research publication that examines current theoretical frameworks, research projects, and empirical studies related to the design, implementation, and evaluation of early warning systems and targeted interventions and discusses their implications for policy and practice. Moreover, this book will review common challenges of early warning systems and dashboard design and will explore design principles and data visualization tools to make data more understandable and, therefore, more actionable. Highlighting a range of topics such as curriculum design, game-based learning, and learning support, it is ideal for academicians, policymakers, administrators, researchers, education professionals, instructional designers, data analysts, and students.
The third edition of this award-winning Handbook continues the mission of its predecessors: to provide a comprehensive compendium of research in all aspects of distance education, arguably the most significant development in education over the past three decades. While the book deals with education that uses technology, the focus is on teaching and learning and how its management can be facilitated through technology. Key features include: Comprehensive coverage that includes all aspects of distance education, including design, instruction, management, policy, and a section on different audiences. Chapter authors frame their topic in terms of empirical research (past and present) and discuss the nature of current practice in terms of that research. Future research needs are discussed in relation to both confirmed practice and recent changes in the field. Section one provides a unique review of the theories that support distance education pedagogy. Section six includes a unique review of distance education as a component of global culture. This book will be of interest to anyone engaged in distance education at any level. It is also appropriate for corporate and government trainers and for administrators and policy makers in all these environments. Recipient of the 2013 IAP Distance Education Book Award
Learning Analytics in the Classroom presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different education domains. Highlighting the real potential of learning analytics as a way to better understand and enhance student learning and with each chapter including specific discussion about what the research means in the classroom, this book provides educators and researchers alike with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This volume is split into five sections, all of which relate to the key themes in understanding learning analytics through the lens of the classroom: broad theoretical perspectives understanding learning through analytics the relationship between learning design and learning analytics analytics in the classroom and the impact it can and will have on education implementing analytics and the challenges involved. Bridging the gap between research, theory and practice, Learning Analytics in the Classroom is both a practical tool and an instructive guide for educators, and a valuable addition to researchers' bookshelves. A team of world-leading researchers and expert editors have compiled a state-of-the-art compendium on this fascinating subject and this will be a critical resource for the evolution of this field into the future.
Through its research-to-practice focus, this book honors the professional contributions of Professor Barry J. Zimmerman as illustrated by the recent selfregulation applications of a highly respected group of national and international scholars. This book will serve as a valuable resource for those interested in empowering and enabling learners to successfully manage and self-direct their lives, education, and careers. In particular, K-12 educators, college instructors, coaches, musicians, health care providers, and researchers will gain invaluable insight into the nature of self-regulation as well as how they can readily apply self-regulation principles into their teaching, instruction, or mentoring. Emergent trends in education and psychology circles, such as linking selfregulated learning assessment and interventions as well as the use of technology to enhance student learning and self-regulation, are additional themes addressed in the book. The kaleidoscope of self-regulation issues addressed in this book along with the wide range of promising intervention applications should also prove to be particularly appealing to graduate students as they pursue their future research activities and seek to optimize their individual growth and development.
