"We use people to find content. We use content to find people."*
On Sept 18 our SIRTEL workshop takes place. It's gonna be "Serious Fun"! Let me just outline why:
SIRTEL'07: Raison d'etre
Recommender systems, as well as social navigation, have been around since the popularisation of WWW, that's some 15-20 years now. The idea is to help people choose the right stuff from a potentially overwhelming set of choices. To facilitate that users could be helped with information from other users, the choices made before (by themselves or similar users), the ratings or reviews other people had done, etc. (Rescnik et al., 1997)
The field of learning technologies has seen recommenders of some sort being discussed and prototyped since the late nineteens. In the review of the field in Manouselis et al (2008) we identified about 10 recommenders, and even more conceptual papers of them, but very little has matierialised so far.
Since the last few years recommenders have made a second arrival into the discussion topics of technology, or network, enhanced learning. Undoubtedly, this has been influenced by the arrival "Web 2.0" with all its ideas:
- Collaborative tagging, for example, has changed lots of ideas of how metadata should be produced and how static a metadata record should be: it's not anymore one metadata record produced by a librarian, but lots of annotational and attentional metadata by lots of users.
- Other annotations by users that express their subjective judgements have seen a huge growth too, we don't only talk about ratings or reviews in their traditional sense, but also tumbs-up or down, giving pokes to people or objects, etc.
- Social bookmarking, which allows users to create easy references to their own collections of digital resources (photos, books, links, music,..), has given a new dimension to the concept of social navigations. The link between resource-user(-tag) allows users to navigate other people's collections and thus find novel resources. Also, the same resource-user-tag link gives researchers an itch to use this information to group similar users for recommendation purposes, as well as to study the emerging networks.
- Expressing social ties between people has also brought new possibilities along. We are not only seeing networks of friends, but there are new possibilities where people can express different networks, ones for professional use, others for personal, recreational, etc purposes. Also, portability of these networks has become an issue discussed for better designs (social-network-portability group, PeopleWeb ,..).
- Something else is also happening behind the scenes. Clicksteam and user behaviour on the Web is not anymore a property of the commercial portal on which users are, but users are starting to take seriously how their "attention" is being used, who owns it, etc. Attentional metadata is a huge source of information that educationalists are also starting to take more seriously and thinking how it could be used for better serving learners and teachers (Contextual Attention Matadata, Attention Profiling Mark-up Language, Attention Trust,..). Attentional metadata can also become crucial when it comes to better understanding the intentions of a user, why are they, for example, looking for some information and for what task at hand!
- Finally, content for educational use, or rather its production, is also seeing a change. Users generate more and more of the content on the Web in general, a trend which is also seen in the e-learning. Of course, traditionally teachers have always produced lots of their own material, but now its re-use also has been facilitated (e.g. repositories/referatories). Also, the collaboration aspect is facilitated by the Web, it has become easier for people to work together on things (e.g. wikis, collaborative platforms,..). Additionally, learners produce plenty of material which also should be seen and used as educational content.
To sum-up: two main topics evolve around social context and social content. Social context is how we express the who, where and with whom, and social content are the objects or digital artefacts that are in the center of the communication, exchange and networks.
All the above has hopefully also changed how we will see the future of social information retrieval for technology enhanced learning. This workshop will all be about that! Serious Fun!
N. Manouselis, R. Vuorikari, F. Van Assche, “Collaborative Filtering of Learning Objects for Online Communities: An Experimental Investigation”, accepted for publication in Computers in Human Behavior, Special Issue on ‘Advances of Knowledge Management and Semantic Web for Social Networks’, 2008.
Resnick P. & Varian H.R., “Recommender Systems”, Communications of the ACM, 40(3),1997