For those who could not make it at all, you can soon find recording on the SIRTEL site.
The workshop had four main sessions:
- We started with a keynote address from people who work with music recommenders. MyStrands people talked about applying social recommender systems to technology enhanced learning. It was an interesting talk that challenged all of us to think what are recommenders for learning purposes in the first place (goal) and what kind of data do we want to use to do that.
As any good keynote, this one gave more ideas to think than answers. It nicely set the base for the further discussions during the workshop that focused on the need to define the field of Social Information Retrieval for Technology Enhanced Learning, and to establish a baseline so that we know what are we really set to do.
- The second session was about Tagging and Visualisation. We had my presentation about the user behaviour on tagging in multiple languages; then there was a presentation from COSL that talked about "Activities of Daily Living on the Web", Brandon also showed a few demos of the widgets that can be used to rate or recommend related content. That was followed by a talk on reward structures to encourage teachers to share open educational material. Finally, we listened about Visualisation of social bookmarks, a work that leads into visualising bookmarks in an educational repository.
- The 3rd session was on Recommender Systems. Here we first heard about some R&D work that OU NL is carrying out using the idea of learning paths to better support learning activities of students. Then, there was a study about using affiliation networks as a mechanism for collaborative filtering (understood largely). This was followed by a study on simulating recommendations based on multi-attribute ratings on learning resources by teachers. Finally, we had a system demo of Daffodil that supports collaborative information seeking.
- The final session was what we called "Enablers and Challenges". It was a discussion session, and as we advanced, it was clear that people had a lot to say. It might even have been better to allow more time for this, but hey, you live and you learn.
- How to define and chart out the area of Social Information Retrieval (SIR) for learning?
- Is this application domain different from other SIR, on micro and macro level?
- What do we recommend?
- In what context?
- and based on what?
- What are the best SIR methods for TEL?
- And what is the data that we should use? The "data issue" was something that was heavily emphasised by the MyStrands folks, who obviously speak of experience.
- The questions rouse also: when do we start implementing these for real or are we just over-engineering and never ready to launch?
- Evaluation and empirical data for real evidences was on the focus a lot.
More will follow. This is quick and dirty now, hopefully I will get more input from people participating in order to get more depth on our summary.