This book constitutes the refereed proceedings of the Second European Conference on Technology Enhanced Learning, EC-TEL 2007, held in Crete, Greece in September 2007. The papers presented were carefully reviewed and selected from 116 submissions. The conference provides a unique forum for all research related to technology-enhanced learning, as well as its interactions with knowledge management, business processes and work environments.
The quality of students’ learning experiences is a critical concern for all higher education institutions. With the assistance of modern technological advances, educational establishments have the capability to better understand the strengths and weaknesses of their learning programs. Developing Effective Educational Experiences through Learning Analytics is a pivotal reference source that focuses on the adoption of data mining and analysis techniques in academic institutions, examining how this collected information is utilized to improve the outcome of student learning. Highlighting the relevance of data analytics to current educational practices, this book is ideally designed for researchers, practitioners, and professionals actively involved in higher education settings.
With emerging trends such as the Internet of Things, sensors and actuators are now deployed and connected everywhere to gather information and solve problems, and such systems are expected to be trustworthy, dependable and reliable under all circumstances. But developing intelligent environments which have a degree of common sense is proving to be exceedingly complicated, and we are probably still more than a decade away from sophisticated networked systems which exhibit human-like thought and intelligent behavior. This book presents the proceedings of four workshops and symposia: the 4th International Workshop on Smart Offices and Other Workplaces (SOOW’15); the 4th International Workshop on the Reliability of Intelligent Environments (WoRIE’15); the Symposium on Future Intelligent Educational Environments and Learning 2015 (SOFIEEe’15); and the 1st immersive Learning Research Network Conference (iLRN’15). These formed part of the 11th International Conference on Intelligent Environments, held in Prague, Czech Republic, in July 2015, which focused on the development of advanced, reliable intelligent environments, as well as newly emerging and rapidly evolving topics. This overview of and insight into the latest developments of active researchers in the field will be of interest to all those who follow developments in the world of intelligent environments.
"Forgive yourself for not having the foresight to know what now seems so obvious in hindsight." -Judy Belmont How often have you caught yourself saying "I wish I knew that" or "If only they knew..."? We have all been there. We can always look back and wish that we could change something, but the key is to use that knowledge and make a difference now. We learn from reflecting on our own experiences and by connecting with other educators to learn from theirs. In Things I Wish [...] Knew, Rachelle Dené Poth has brought in fifty educators with different experiences and backgrounds in education to share something they wish they or others knew. Each vignette shares an eye-opening experience, a valuable lesson learned, advice for overcoming challenges, or simply offers some inspiration or words of wisdom. Throughout this book, you will learn from educators who hope to help others make a difference, to make some changes in their practice, and to avoid missing out on opportunities. The book explores things that each educator wishes they knew when they started teaching, something they wish that administrators knew, or things that they wish all students knew. I hope that this book will lead you to reflect on your own practice and inspire you to share your story too.
"This reference brings together an impressive array of research on the development of Science, Technology, Engineering, and Mathematics curricula at all educational levels"--Provided by publisher.
This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques.
In der E-Learning-Domäne bilden sowohl die Lernressourcen, Lehrende und Lernende als auch die stattfindenden Lernprozesse in ihrer Gesamtheit Lernökosysteme. Diese Dissertation untersucht die Modellierung von Lernökosystemen zur Unterstützung ihrer Aggregation und Wiederverwendung. Zur Erreichung dieses Ziels müssen Modelle von Lernökosystemen die Aggregierbarkeit, Austauschbarkeit, Interoperabilität und granulare Wiederverwendbarkeit ihrer Daten unterstützen. Auf Basis durchgeführter Nutzerstudien werden Konzepte digitaler Modelle von Lernökosystemen, sogenannte LOOCs (Linked Open Online Courses), entwickelt. Dabei werden insbesondere Technologien des Semantic Webs sowie Linked-Data-Konzepte betrachtet. Die entwickelten ontologischen Modelle bilden die Basis für mehrere E-Learning-Applikationen, welche die Tragfähigkeit der Konzepte sowie eine hohe Nutzerakzeptanz zeigen. Ferner wird ein formales Interpretermodell für CSCL (Computer-Supported Collaborative Learning) Scripts zur Beschreibung von Lernprozessen, welches mit Hilfe von Abstract State Machines spezifiziert wurde, vorgestellt. In the e-learning domain, the learning resources, teachers and learners and the active learning processes in their entirety construct the learning ecosystems. This thesis examines the modelling of learning ecosystems to support their aggregation and reuse. To achieve this goal, learning ecosystem models must support aggregation, compatibility, interoperability and granular re-usability of their data. Through user studies, digital model concepts of learning ecosystems, i.e. so-called LOOCs (linked open online courses), were developed. In particular, Semantic Web technologies and Linked Data concepts are considered within the context. The developed ontological models form the basis for a number of e-learning applications that show the viability of the concepts as well as a high user acceptance. Further, a formal interpreter model for CSCL (Computer-Supported Collaborative Learning) Scripts for the description of learning processes specified by using Abstract State Machines is presented.
Offering the latest developments in online education in the era of big data, this book explores theories, technologies, and practices in the field of data-driven online learning support services using learning analytics. This book is divided into five chapters. Chapter 1 reflects and reconstructs the connotation of learning support against the backdrop of education reform, the rise of learning analytics, and the upgrading of the demand for learning services in the new era. Chapter 2 presents a P-K-DSE-E model of online learner characteristics and discusses measurement and data representation methods for learner characteristics based on it. Chapters 3–5 focus on the three types of learning support that are closely related to learning performance and satisfaction, including the promotion of social learning, electronic learning assessment based on the learning process, and personalized tutoring and support. This book innovatively develops the concept, theory, and practical methods of student support services in distance education traditional practices in the new era and provides valuable exploration of data-driven personalized learning service methods and technologies in the era of artificial intelligence through rich examples. This book will be essential reading for students and scholars of distance and online education, educational technology, and audiovisual education.
This handbook provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It helps education experts understand what types of questions EDM can address and helps data miners understand what types of questions are important to educational design and educational decision making.
