20101210-NodeXL-Twitter-pdfleaks by Marc_Smith, on Flickr
Creative Commons Attribution 2.0 Generic License by  Marc_Smith

I am about to embark on my third massive open online course (MOOC) which starts next week.  The course is an introduction to Learning and Knowledge Analytics, a burgeoning area of interest for educational technologists.  The course is facilitated by George Siemens (TEKRI, Athabasca University), Jon Drown (SCIS, Athabasca University), Dave Cormier (University of Prince Edward Island), Tanya Elias (Athabasa University), and Sylvia Currie (BCcampus).

I have not registered or paid a fee for this course as it is not offered in the traditional sense that a course would be from a university.  The course runs virtually, using synchronous discussion through Elluminate (an online realtime web conferencing system) and asynchronous discussion through blogs, twitter, and discussion forums.  The organizers have created an opportunity for anyone interested in this topic to gather together and discuss Learning and Knowledge Analytics using the aforementioned technologies.  The MOOC is a new model for educating online which uses freely available and mostly open source software for communication, and open educational resources for content.  Participants are encouraged to reflect on the discussions and readings on their own blogs, or websites using a hashtag (#LAK11)  The hastag enables people to aggregate content from the course by searching for the unique identifier (the hashtag).

Check out this video by Dave Cormier for more information on what a MOOC is.

Amazingly more than 400 people have signed up for the course from all around the world.   I did a quick visual of the 100 or so people who have so far introduced themselves in the forum using ManyEyes.  You can view the interactive image here.

The course agenda is as follows:

Week 1 (Jan 10-16): Introduction to Learning and Knowledge Analytics
Week 2 (Jan 17-23): Rise of “Big Data” and Data Scientists
Week 3 (Jan 24-30): Semantic Web, Linked Data, & Intelligent Curriculum
Week 4 (Jan 31-Feb 6): Visualization: Tools for, and examples of, Analytics
Week 5 (Feb 7-13): Organizational implementation
Week 6 (Feb 14-20): What’s next for Learning & Knowledge Analytics?

I have some experience as a data analyst and statistician.  I was involved with setting up a data warehouse in my previous position and this required me to work with massive amounts of data in excel, and SQL Server.  As geeky as it sounds I enjoy working with masses of data and trying to extract information and intelligence through analytics.

When we interact online a ginormous amount of data is created as we navigate, connect, register, and share.  In an educational context we may start using that data to optimize learning, intervene, provide formative evaluation, scaffold, etc.

In my current role we use Google Analytics (GA) to track our online elearning content keeping an eye on number of visits, hits on content, visitor location, time on site, and exit points. Our content creators are quite interested to see that their resources are being accessed throughout the world. Unfortunately we can’t yet tell them what exactly they are being used for, unless we get a comment or some follow up.

We actively monitor our search logs to see what people are searching for when they visit our websites. Whether it is students from our university or others around the world, it is really remarkable reviewing the types of content people expect (or hope) to find on our site. A few weeks back we started to see a number of searches for ‘referencing’, ‘citation guide’ so we worked with our library to make their already online citation guide open content with a Creative Commons license. I think there is a space for predictive analytics wherever search is conducted. Certainly in the library where students often begin with search, we could be using that data to predict patterns in the way resources are used.

I’m really looking forward to the course.  Expect some geeky posts in the coming weeks.

Learning and Knowledge Analytics 2011

CC BY 4.0 Learning and Knowledge Analytics 2011 by Michael Paskevicius is licensed under a Creative Commons Attribution 4.0 International License.

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