Notes from Computer-Supported Collaborative Learning conference 2011

July 21, 2011, [MD]

This was my first year attending the bi-annual CSCL conference, which this year happened to be at the Hong Kong University campus. I was very excited, since I had been reading papers by many of the people who would be attending, and it would also be the first time I'd be in Hong Kong (and later China) with my supervisor, and people from my university.

Although the actual core conference only lasts for a few days, I began my participation with two days of pre-conferences, attended post-conference events in both Guangzhou and Beijing, and even the doctoral summer school in Beijing that was affiliated with the conference. Thus, my earliest notes are from the pre-conference on machine learning and data analysis on July 4th, and my latest ones from Gerry Stahl'stalk to the international summer school on July 18th.

However, there were of course sessions I did not capture notes for. Taking detailed notes is exhaustive, and it's difficult to do it the entire day. This is added to mundane issues like finding power outlets, etc. Either way, I hope the notes might be helpful - they certainly are to me. Overview over all notes.

The first pre-conference which I mentioned above was organized by Carolyn Penstein Rosé and her post-doc Gregory Dyke, and discussed tools to analyze computer-mediated communications. We got training in using Tatiana, a tool to analyze synchronous events with time-coded data from multiple media (for example videos, transcripts, chat and a shared whiteboard). In the afternoon, we learnt to use SIDE, which is a GUI for a machine-learning framework. Although nobody can become an expert in machine-learning in one afternoon, it was a great overview of the state of the art of machine learning, giving you a sense of what kinds of problems machine learning might be appropriate for. (For people interested in ML, [@mclaren2010supporting] is a great paper showing how ML can be applied to a specific educational challenge, and the thinking that went in to choosing the right algorithm).

The second pre-conference was about connecting levels of learning, organized by Dan Suthers, Chris Teplovs, Marten de Laat, Jun Oshima and Sam Zeini. I've read about these ideas before, in [@suthers2010framework], and found them interesting, but quite complex. In this workshop, Gerry Stahl gave a great historical/philosophical overview over CSCL as a discipline, and Dan Suthers presented on their theoretical approach. Then, a few datasets had been shared between researchers who provided different analyses of them - very interesting (although not always easy to tie back to the original theoretical framework of the session).

Ed Chi from Google Research opened the conference with an interesting keynote on augmented social cognition, with several neat cases from his work with access to huge data sets. From the conference sessions, I managed to capture two very interesting sessions on technology-enhanced interactions & analysis (1, 2), and one session on MUPEMURE, a "Model of Computer-Supported Collaborative Learning with Multiple Representations".

There were some very interesting presentations about the future of Knowledge Forum in the Guangzhou post-conference, which I did not manage to capture (but check out these slides 1, 2). I did get some notes from two of Gerry Stahl's presentations, one describing two case study analyses he did, and one on the history and future of CSCL.

I'm looking forward to the International Conference on Learning Sciences next year in Sydney (CSCL and ICLS alternate every other year), where I hop to present a paper on open learning environments. I'm also planning to dig into all the notes I took, and all the connections I made, read more papers, etc.


Stian Håklev July 21, 2011 Toronto, Canada
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