Special Issue on Social Information Retrieval for Technology Enhanced Learning

Special Issue on Social Information Retrieval for Technology Enhanced Learning

Guest Editors: Riina Vuorikari, Nikos Manouselis, Erik Duval


Social information retrieval (SIR) refers to an approach that assists people in obtaining relevant information by harnessing the knowledge or experience of colleagues, friends, peers, and others. SIR applications like collaborative filtering and social bookmarking rely on social network analysis and the use of subjective relevance judgments such as tags, annotations, ratings and evaluations. They are widely deployed on the World Wide Web, for instance in entertainment and e-commerce.

SIR methods, techniques and systems open interesting new approaches for learning and teaching. There is an abundance of content, people (e.g. other learners, experts, tutors) and other resources (e.g. lesson plans, visualization software) that can be used to facilitate teaching and learning. The challenge is to develop, deploy and evaluate SIR systems that provide learners and teachers with suitable learning resources from a potentially overwhelming variety of choices.

The Workshop on Social Information Retrieval for Technology-Enhanced Learning (SIRTEL07) served as the first venue that focused on research questions around the application of SIR methods, techniques and systems in Technology Enhanced Learning (TEL). SIRTEL07 was organised in the context of the 2nd European Conference on Technology Enhanced Learning (ECTEL07), on September 17, 2007 in Crete, Greece. Its main goal was to bring together researchers and practitioners, in order to assess the current status of research related to the application of SIR in educational settings. The workshop was followed by SIRTEL08 in Maastricht in September 2008.

The first workshop gave impetus for a Special Issue of the Journal of Digital Information (JoDI) to present the state-of-the-art of this exciting new and emerging field. In addition to revised versions of the workshop papers, two other papers were invited from researchers who contribute actively to this field. After a rather demanding review process with three reviewers per submission and two review rounds, we were very happy to conclude with five excellent papers that address several aspects of SIR techniques and their application within the context of Technology Enhanced Learning.

The first paper, "Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning" by H. Drachsler, H. G. K. Hummel and R. Koper focuses on the context of Learning Networks and outlines a number of important distinctions between personalising recommendations for learners and for consumers. The second paper also contributes to the specific educational context for recommendations: "The Pedagogical Value of Papers: a Collaborative-Filtering based Paper Recommender" by M. Tang and G. McCalla discusses the pedagogical features necessary to make appropriate recommendations of papers to students.

The following paper by J.Dron and T.Anderson, "Lost in social space: Information retrieval issues in Web 1.5", describes how a rich social application is used to support a distance-taught course. It discusses the difficulties that social technologies pose in information organisation and retrieval when used for formal learning.

The last two papers concentrate on social bookmarking and tagging activities within an educational context. "Exploratory Analysis of the Main Characteristics of Tags and Tagging of Educational Resources in a Multi-lingual Context" by R.Vuorikari and X.Ochoa explores how tags and social bookmarks can be used to help discovery of educational resources across country and language borders. "Visualising Social Bookmarks" by J. Klerkx and E. Duval describes the use of a cluster map visualisation technique to identify tag and community structures and to visualise them.

We would like to take this opportunity to thank all the authors who submitted their papers to the Special Issue. We particularly thank the authors of accepted papers for their high-quality work and for having worked on a tight schedule to come up with their revised versions in a timely manner. We would also like to thank all the reviewers of the submissions in this Special Issue.

Finally, we would like to thank the editors of JoDI (Cliff McKnight and Scott Phillips) for the warm acceptance of this Special Issue idea and the support throughout the whole editorial process.


October 2008

Riina Vuorikari, Nikos Manouselis, Erik Duval

Guest editors