Starting to dig

Educational Data Mining (EDM) has become my life... I am working on a PhD in Instructional Technology at Utah State University and my dissertation proposal is nearing completion. The current title:

"Web Usage Mining: Application to an Online Educational Digital Library Service"


I'll post a link to the defended proposal. But for now, the gist is:

1. There is a ton of educational data out there that is just waiting to be mined.
2. I have been working with the Instructional Architect for the past 5 years and have some experience with web metrics, but now it is time for some serious mining to characterize our users.
3. We have some suspicions as to what user segments exist, but we don't know. Therefore I'll be using an unsupervised machine learning technique on our data (e.g., LCA, SOM).
4. The data will come from our user database, web server logs, and Google Analytics (GA).
   
5. The results of this research should be helpful to (a) the IA tool development, (b) the IA team's teacher professional development workshop, and (c) the digital library community.

In the blog, there will be a page of links and resources as I find interesting places, applications, and ideas about EDL.

It has been interesting how many people are interested in EDM at USU and elsewhere. Both Jamison Fargo and Yong Seog Kim are working with me on the methods and such. As it turns out there are 3-4 other PhD students at USU that have the same kind of interest. We'll have had some great conversations and continue to help each other out. Working with the folks at the National Science Digital Library, we have had some good publications and experience talking about web metrics and user understanding.

Well, there it is for this post. Now on to the good resources...