Learning Analytics Course #LAK11 – Final Thoughts

I have just completed my first Massively Open Online Course (MOOC), Learning and Knowledge Analytics taught by George Siemens of the University of Athabasca. Participating in a course of this format is both challenging and rewarding. I did not participate to the level that I had wanted to (2-3 hours per week vs the recommended 4-5) but I made sure that I stuck it out to the end. I had two goals for the course that I would like to discuss here: 1) to examine the MOOC format with the idea of using part or all of it’s features for future projects and 2) to examine the scope and potential of Learning Analytics as a possible service to make available to clients. I accomplished these goals even though I did not participate in the course as much as I wanted to. Here are my thoughts:

The MOOC format works like this: An instructor or team of instructors/moderators/mentors decides to provide a MOOC and makes it open to anyone on the Internet. Learners register for the course by joining a Google group so that they can get updates from the instructor(s) by email. The instructor(s) provides content and structure via whatever tool is best suited. In this course there was a discussion board on Moodle, Webinars on Elluminate, an Instructor’s blog and aggregation of content on Netvibes. The participants are encouraged to expand their participation into their own social media tools (Twitter, WordPress, Facebook, Flickr, Youtube etc.). The important mechanisms to make this a unique and powerful experience are: 1) the fact that anyone around the world can join, which opens up the conversation; 2) the tools are readily available and expandable; 3) the participation of the learners is key to the creation of the content.

I attended most webinars and participated in the chat area that runs along side the presentation. This is the way that the guest speaker can get feedback on what they are saying. Those realtime discussions were the most interesting part of the course. I read some of the recommended reading and some blog postings by participants. I tried some of the tools and joined in some of the online discussion boards. I got a great return on my investment because I could fit the work into my limited schedule and still get great insights and resources for future work. I got the added benefit that many of the participants were in academia and so I got a flavor for the different challenges they face in that environment.

The Learning Analytics material was premised on the idea that as learning activity moves more online, learners are leaving behind a trail of data of sufficient size to support useful analysis. One of the primary examples was the Signals program at Purdue. They used data that correlated online activity with course success and used that information to help at risk students. There is almost as much potential in this idea as there is data to support it. The question becomes to what purpose do you wield this power. The ideas in this course were often in danger of being solutions in search of problems. Often the conversation brought up the recent existential angst of Learning Management Systems since they are the most likely repositories of data for formal learning programs. The bottom line for both analytics solutions and the tools they deploy is that learning takes resources, time or money, and people are accountable for outcomes from those resources. Data analysis is a tool to extract value from that activity in order to justify the spend. The analysis can then lead to decision making that increases the effectiveness of that spend.

The other issue that kept coming up for me was a matter of scale. Using data about course preferences to guide learners in choice selection (similar to Amazon’s “People who bought this also bought this…”) is of a scale that is radically different from examining the outcome of increasing college completion rates for an entire country, yet this was the scope of the course. Questions of ethics costs, tools, and usefulness have varying results based on these changes in scale. George Siemens suggested reducing the scope of the course next time but I don’t agree. This was a great overview of the area of study. I just think scale is an important subject to cover.

I plan on going back to the material to see how I can use it to offer more services to my corporate customers. I’d like to participate in another MOOC when I have time. We are very fortunate to live in an age when these new forms are accessible to anyone.


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