July-September 2009 (VOL. 2, No. 3) pp. 167-167
/09/$31.00 © 2009 IEEE

Published by the IEEE Computer Society
Wolfgang Nejdl

Peter Brusilovsky
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Dear Readers,
Welcome to our third issue this year, which includes a set of eight papers exploring advanced technologies for e-learning and new forms of education using these tools. The broad set of topics covered in these papers stresses the diversity of the field, which currently encompasses a wide a range of different technologies.
Collaborative online learning has been a key aspect for technology-enhanced learning since the beginning of the Web. This issue features two papers related to this topic.
Youngmoo E. Kim, Travis M. Doll, and Raymond Migneco from Drexel University present two innovative online activities, which allow students to explore different sound and acoustics concepts, and evaluate it in a pilot study with middle school students.
CoScribe, discussed in the paper by Jürgen Steimle (PARC), Oliver Brdiczka, and Max Mühlhäuser (TU Darmstadt), focuses on the collaboration of knowledge workers. The prototype system combines work with printed and digital documents in an innovative way and allows users to collaboratively annotate, link, and tag printed and digital documents. The system has been evaluated in user studies and provides for efficient annotation as well as the structuring and retrieval of documents.
The next two papers address the issue of defining, planning, and personalizing the online educational process.
Iván Martínez-Ortiz, José-Luis Sierra, and Baltasar Fernández-Manjón from the Complutense University of Madrid explore an approach based on IMS Learning Design, the current standard language for providing a description of educational processes. Their paper presents an e-LD system, which provides a graphical notation to develop learning designs, allows the reengineering of IMS LD learning designs, and includes a tool to generate and analyze dependencies between different IMS LD elements.
An alternative approach based on the ideas of dynamic sequencing and adaptive hypermedia is explored by Carla Limongelli, Filippo Sciarrone, Marco Temperini, and Giulia Vaste. Their paper introduces LS-Plan, a framework for personalized e-learning, which considers student learning style and knowledge level to deliver a personalized course for every learner.
Technology-enhanced learning tools can also provide in-depth feedback through extensive simulations. Focusing on medical education, Yuh-Ming Cheng (Shu-Te University), Lih-Shyang Chen, Hui-Chung Huang, Sheng-Feng Weng, Yong-Guo Chen, and Chyi-Her Lin (National Cheng Kung University, Taiwan) describe their implementation of a pedagogical agent, the HINTS simulation system, which provides just-in-time adaptive feedback to medical students. The system has been installed in the National Cheng Kung University Medical Center with promising results.
In the paper “Quantitative Analysis of Learning Object Repositories,” Xavier Ochoa and Erik Duval conduct a detailed study on the process of publication of learning objects in repositories. They take size, growth, and contributor base into account, and present the distributions found for five types of repositories. In their conclusions, they discuss the implications these findings could have in the design and operation of learning object repositories.
A totally different, yet equally relevant topic is discussed by Adel Khelifi, Manar Abu Talib, Mohamed Farouk, and Habib Hamam from the United Arab Emirates. Their Open University Project aims at providing appropriate open source software which can be used in the higher education sector, with appropriate financial advantages, especially for developing countries.
Finally, Nikos Tsianos, Zacharias Lekkas, Panagiotis Germanakos, Costas Mourias, and George Samaras from Greece assess the use of cognitive and affective factors in adaptive educational hypermedia. They take into account cognitive style, eye gaze behavior, visual working memory span, and control/speed of processing and anxiety in an adaptive educational system. Based on their experiments, adaptation on these parameters through personalization techniques may have a positive effect on learning performance.
We hope you again enjoy this issue, and we are looking forward to receiving your submissions, both to regular issues as well as on our special-topic-focused calls, as announced on the TLT website.
Wolfgang Nejdl, Editor-in-Chief
Peter Brusilovsky, Associate Editor-in-Chief

For information on obtaining reprints of this article, please send e-mail to: lt@computer.org.