Learning Analytics is an emerging topic of interest throughout all levels of education focusing on how to harness the power of data mining, interpretation, and modeling.
However, there are several similar terms (academic analytics, predictive analytics, business intelligence, etc.) that can confuse educators and administrators alike. In this session, we will unpack this new area of interest and discuss how institutions can begin to leverage available products and open source communities to utilize analytics to improve understandings of teaching and learning and to tailor education more effectively.
We will briefly present an overview of the learning analytics field, drawing from popular examples such as the Signals project at Purdue U. and the Check My Activity tool at U. Maryland, Baltimore County. We will also review the structure of Sakai CLE and OAE user-level metrics and briefly discuss projects to design and implement tools to utilize these metrics in meaningful ways.