Martin Wolpers

Erik Duval

Ralf Klamma

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.

Second European Conference on Technology Enhanced Learning, EC-TEL 2007, Crete, Greece, September 17-20, 2007, Proceedings

Creating New Learning Experiences on a Global Scale

Mike Sharples

Rosamund Sutherland

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.

Research Themes

Technology Enhanced Learning

Katrien Verbert

Nikos Manouselis

Hendrik Drachsler

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.

Recommender Systems for Learning

Erik Duval

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