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Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.
"This book aims to provide a comprehensive review of state-of-the-art practices for educational recommender systems, as well as the challenges to achieve their actual deployment"--Provided by publisher.
This book gives an overview of the state-of-the-art in Technology Enhanced Learning (TEL). It is organized as a collection of 14 research themes, each introduced by leading experts and including references to the most relevant literature on the theme of each cluster. Additionally, each chapter discusses four seminal papers on the theme with expert commentaries and updates. This volume is of high value to people entering the field of learning with technology, to doctoral students and researchers exploring the breadth of TEL, and to experienced researchers wanting to keep up with latest developments.
This book explains how educational research can inform the design of technology-enhanced learning environments. After laying pedagogical, technological and content foundations, it analyses learning in Web 2.0, Social Networking, Mobile Learning and Virtual Worlds to derive nuanced principles for technology-enhanced learning design.
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.
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.
Technology-enhanced learning is a timely topic, the importance of which is recognized by educational researchers, practitioners, software designers, and policy makers. This volume presents and discusses current trends and issues in technology-enhanced learning from a European research and development perspective. This multifaceted and multidisciplinary topic is considered from four different viewpoints, each of which constitutes a separate section in the book. The sections include general as well as domain-specific principles of learning that have been found to play a significant role in technology-enhanced environments, ways to shape the environment to optimize learners’ interactions and learning, and specific technologies used by the environment to empower learners. An additional section discusses the work presented in the preceding sections from a computer science perspective and an implementation perspective. This book comes out of the work in Kaleidoscope: a European Network of Excellence in which over 1,000 people from more than 90 institutes across Europe participate. Kaleidoscope brings together researchers from diverse disciplines and cultures, through their collaboration and sharing of scientific outcomes, they are helping move the field of technology-enhanced learning forward.
As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years. Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices. Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.
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.
This volume provides an up-to-date study of theory and practice on the importance of technology in teaching and learning. The contributions are carefully peer-reviewed from over 100 submissions to the International Conference on Teaching and Learning 2006, held in Hong Kong. Sample Chapter(s). Chapter 1: Faculty Perceptions of ICT Benefits (391 KB). Contents: Faculty Perceptions of ICT Benefits (R Fox et al.); Thinking about Thinking Online (K Downing et al.); Teacher''s Sharing Pedagogical Experiences in a Learning Environment that Supports Self-Regulated Learning (G Dettori et al.); Online Interaction: Trying to Get It Right (L Chow and R Sharman); Crossing Borders: How Cross-Cultural Videoconferencing can Satisfy Course Goals in Dissimilar Subjects (J S Wilkinson & A-L Wang); The Evaluation of Information and Communication Technology Use in Professional Schools (P Gabor & C Ing); Using Technology in Education: The Application of Data Mining (K H Chye et al.); A Comparison of WebCT, Blackboard and Moddle for the Teaching and Learning of Continuing Education Courses (K S Cheung); The Object-Oriented Database Application and the System Architecture of a National Learning Objects Repository for Cyprus (P Pouyioutas et al.); and other papers. Readership: Graduate students, researchers and practitioners involved in the development and education of e-learning.