Over the years, I have been interested in scholarly workflows and, more recently, knowledge infrastructures – for both knowledge workers and young learners. It has become a hobby for myself to reflect on my own workflows and explore tools that I could add to improve my scholarly practice. I was interested enough in this topic to give a talk on this topic (in Mandarin) last summer. Annotation software as knowledge infrastructure Annotation is, and has always been, an important part of knowledge processes.
This year’s Knowledge Building Summer Institute (KBSI) is going to be special. First, it’s held near the end of November, for the first time in summer for folks from the Southern Hemisphere. Second, the conference is going to be virtual, following a hybrid synchronous–asynchronous model. Much work will be done in Knowledge Forum asynchronously before interactive sessions in Zoom on the conference days. Last but not least, this year’s conference will feature a global KB design experiment, Saving the Planet, Saving Lives, led by colleagues from Ontario and Singpapore.
First of all, I’d like to thank our JLA editors-in-chief and SoLAR for organizing this webinar, and more events to come on the topic of rigor. As a community, learning analytics has grown substantially and to a great extent matured since it emerged around 10 years ago. Thanks to tremendous work by colleagues, we have an annual conference, a professional society, an established journal, and probably even more importantly, significant interest in our field from society.
In response to a special call for papers from Information and Learning Sciences, a team of us rallied and wrote a review article about Using Social Annotation in Online Classes ( see preprint). It was an interesting challenge given the short timeframe. But we eventually pulled this off as a team thanks to Xinran Zhu’s strong leadership and everyone’s dedication to this work. In this blog post, I won’t talk about what we wrote.
In a chapter to be included in the 2nd edition of the Handbook of Learning Analytis, Dr. Stephanie Teasley and I tried to write about Collaboration Analytics in a way that integrate ideas from CSCL, CSCW, learning sciences, and learning analytics. Below is a draft abstract of the chapter. In this post, I am sharing a key message from this chapter – a map of collaboration analytics – and invite you to provide me feedback and suggestions.