This group provides a platform to discuss, provide feedback on, request new, etc. podcasts in the STELLAR podcast series.

This will be the main entry point for the community around the "Ground-breaking ideas in TEL" Special Issue that is being prepared for the International Journal of Technology-Enhanced Learning (ijTEL).

The activities for this group include: collaborative work on the call for papers/reviewers for the special issue, a "ideas clinic" for contributions to the special issue, as well as an experimental open review process to be held publicly through this community website.

This is the hub for information and news on the use of TEL in formal education.

This group serves as an aggregator of information on learning tools. It will try to indicate latest trends.

This group is for students who are participating in JTEL Summer school and are in the "Strengthening Learning Contexts" team.

This group is for students who are participating in JTEL Summer school and are in the CONNECTING LEARNERS team.

This is a group dedicated for discussions over a students' presentation on 'Orchestrating Learning' in the context of JTEL summer school 2010

Introduction
As a follow-up to a successful workshop on the same theme at ECTEL09, we are organizing a workshop on Research2.0 approaches to TEL research at ECTEL10.

Research2.0 is in essence a Web2.0 approach to how we do research. Research2.0 creates conversations between researchers, enables them to discuss their findings and connects them with others. Thus, Research2.0 can accelerate the diffusion of knowledge.

Topics for this workshop include, but are not limited to:

• Evaluation of existing Research2.0 tools and infrastructures from a TEL perspective
• Development of TEL-related use case scenarios for Research2.0 tools and infrastructures
• Influence of Research2.0 tools and technologies on scientific practices in TEL
• Formats and protocols for Research2.0 data exchange (linked data, RSS, BuRST, …)
• Ownership and privacy of research information
• Practices of the diverse Technology Enhanced Learning disciplines, and how Research2.0 can influence them

Format
Authors are invited to submit original unpublished work. The following types of contributions are possible:

• Short papers (3-5 pages) that state the position of the authors on issues relevant to the workshop or work in progress, even when in very early state.
• Full papers: (8-12 pages) that describe problems, needs, novel approaches and frameworks within the scope of the workshop. In this category, empirical evaluation papers and industrial experience reports are welcome for submission.

Each presenter will be linked to related papers from other presenters and will be asked to compare in the presentation how the works of others relates to their own work.

The presentation of unfinished ideas, tools under development and especially failures is explicitly encouraged. This includes the presentation and discussion of tools and their real-world usability.

The aim of this group is to:

• facilitate discussions among participants before and after the conference;
• post submitted papers for an open peer review;
• publish information and news about the workshop;
• collect reactions through social media on the workshop.

All presentations and discussions will be broadcast via Flashmeeting to attract more feedback, and to document the event. Online questions and comments will be explicitly taken into account during the workshop.

First steps:

To get you started see the short notice "First steps for the Research 2.0 workshop" in the "Group page" section at the bottom of this page.

Twitter, Delicous, etc.

The hashtag for this event and for further information sharing is: #res2tel (Research 2.0 for technology-enhanced learning)

As a short URL to this page you can use: http://qone.eu/s2t

Important Dates

The submission deadline for the workshop papers is extended!

• Paper submission: 27 June 2010 04 July 2010
  
• Paper acceptance: 11 July 2010 18 July 2010
• Final camera ready: 04 September 2010
  
• Workshop date: 28 September 2010

Paper submission and questions
Please submit your paper at http://www.easychair.org/conferences/?conf=research20.

Feel free to contact erik.duval@cs.kuleuven.be if you have any questions!

Programme Committee

• Erik Duval (http://erikduval.wordpress.com)
• Xavier Ochoa (http://ariadne.cti.espol.edu.ec/xavier)
• Wolfgang Reinhardt (http://isitjustme.de)
• Nina Heinze (http://www.twitter.com/sywot)
• Fridolin Wild (http://kmi.open.ac.uk/)
• Thomas Ullmann (http://kmi.open.ac.uk/)
• Peter Scott (http://kmi.open.ac.uk/)
• Stefanie Lindstaedt (http://www.know-center.at/)
• Peter Kraker (http://www.know-center.at/)
• Frederik G. Pferdt (http://www.pferdt.de/)
• Johannes Metscher (http://www.imb-uni-augsburg.de/johannes-metscher)
• Andreas S. Rath (http://www.xing.com/profile/AndreasS_Rath)

Recommender systems are increasingly applied in TEL research (e.g. TENCompetence, APOSDLE, ROLE) to personalise learning content and to find suitable peer learners according to their context (individual needs, preferences and learning goals). In the world of commercial recommender systems, it is a common practice to use public available datasets with specific characteristics (e.g. MovieLens, Book-Crossing, or the EachMovie dataset) to evaluate recommender system algorithms. These datasets are used as benchmarks to develop new recommendation algorithms and compare their effects to other algorithms in a standardised way. In TEL there is not one dataset publicly available neither for formal learning nor for non-formal learning settings. Therefore, the goal of the Theme Team is to take an initiative to create benchmarks for TEL recommender systems for the development of uniform evaluation procedures, develop overview methods to monitor how algorithms performed on certain datasets, and to collect and exchange datasets from formal to non-formal learning.

The Theme Team
dataTEL is a Theme Team funded by the STELLAR network of excellence. The Theme Team is consists of six members namely Riina Vuorikari, Katrien Verbert, Stephanie Lindstaedt, Nikos Manouselis, Martin Wolpers and Hendrik Drachsler who have a long time expereinces in the field of recommender systems for Technology-Enhanced Learning (TEL).
The topic of benchmarking recommender systems for TEL is mainly related to two STELLAR Grand Challenges 1. Connecting Learner and 2. Contextualisation.
The selection of most suitable information from the overwhelming amount of information in the network is a challenging task. Furthermore, connecting learners in the network is very important to overcome their isolation and to create effective learning communities. For both tasks contextualised information of learners need to be captured and exploited in order to create personal recommendations for learners. Recommender systems are promising towards these challenges as their technologies match users on defined characteristics and create a kind ‘neighborhood’ of like-minded users. In that way, recommender systems extract contextual information and offer valuable data to suggest suitable peer learners. 

Objectives
The main objective of the Theme Team is to standardise the research on recommender systems in TEL by creating suitable benchmarks. Therefore, the Theme Team has to provided answers to the following five core questions:

1. How can datasets be shared according to privacy and legal protection rules?
2. How to development a respective policy to use and share datasets?
3. How to pre-process datasets to make them suitable for other researchers?
4. How to define common evaluation criteria for TEL recommender systems?
5. How to develop overview methods to monitor the performance of TEL recommender systems on datasets?

Addressing this agenda will improve the development and comparison of recommender systems in TEL and standardise the research on the personalisation of learning.
The Theme Team will integrate different TEL research communities beyond Europe by inviting experts from related research projects that have experiences with data sharing e.g. Grouplens research group at the University of Minnesota.