After the successful edition of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010) we are organizing this second edition again in conjunction with the EC-TEL community.

As already confirmed at RecSysTEL 2010, recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. There are plenty a resource available on the Web, in terms of digital learning content, services and people resources (e.g. other learners, experts, tutors) that can be used to facilitate teaching and learning tasks. The challenge 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.

The previous edition moved a step forward in this research line, but there is still need for joining the ever increasing number of researchers working on TEL recommenders to share our progress and go further. By using this recommendation technology, this workshop can contribute to answer this edition EC-TEL research questions, refined as follows:

• -How can TEL recommenders support people for the technology-rich workplace after they have left school?
• -How can TEL recommenders promote informal and independent learning outside traditional educational settings?
• -How can TEL recommenders apply next generation social and mobile technologies to promote informal and responsive learning?

In this context, several questions are being researched around the application of recommender systems in TEL, such as:

• -Which are the user tasks that may be supported by recommender systems in TEL settings?
• -What should be the focus of recommendation in TEL - resources, people or both?
• -What are the requirements for the deployment of recommender systems in a TEL setting?
• -What is needed to create a set of public available data sets ranging from formal to non-formal learning settings for TEL recommender systems?
• -Can successful recommendation algorithms and systems from other application areas be applied in TEL and what should be the education related requirements taken into account when doing so?
• -How to define evaluation criteria for TEL recommender systems?
• -How can the success of SIR systems can be evaluated in the context of teaching, learning and/or TEL community building?

Therefore, topics include, but are not limited to:

• -User tasks to be supported by recommender systems in TEL
• -Focus of recommendation in TEL
• -Requirements for the deployment of TEL recommender systems
• -Publicly available data sets for TEL recommender systems
• -Recommendation algorithms and systems for TEL
• -Transfer of successful algorithms and systems from other application areas
• -Evaluation criteria and methods for TEL recommender systems