This session will present an overview of the multiple uses of the different types of user information generated by Sakai. Our goal is to demonstrate that this kind of information is usable and informative for improving the overall user experience and understanding how users interact with the system. Monitoring, reporting, analysis, research, and end-user implications will be discussed.
Out of the box, Sakai generates a whole host of information and data logs detailing user activity and actions, database usage, client information, etc. At face value, this information would appear to have only cursory informational significance. However, as we will demonstrate in this session, this data is critical for understanding how users interact with Sakai and can provide information that can help improve the overall user experience.
Beginning with an overview of the kinds of data Sakai collects, we will generally describe the different kinds of data accessible from Sakai administrators and support staff. We will also describe how this information can be used to monitor overall system usage through summary reports and real-time graphing. These monitoring activities are not only valuable for addressing alarming situations (e.g., database usage shooting up 300%) but also understanding what "normal" use is for the local implementation which can, in turn, inform development and load testing.
We will also focus on how the data generated by Sakai can be used to inform institutional research efforts and day-to-day user support efforts. We will discuss how to aggregate and analyze thousands of users and site-level activity into understandable and actionable analyses that can inform a variety of different stakeholders. We will also discuss simple log queries to search for "lost" submissions of student assignments and how many students accessed particular files.
Our final portion of our session will focus on how end-users can take advantage of user logs and inform their Sakai use for teaching and learning. Tools such as SiteStats and CANS will be discussed for their utility in informing how the information gleaned from the logs can act as a catalyst for improving instruction and student learning.
Session slides are available in PDF format here
(rpaditya) slides are available here.
The UM CTools infrastructure statistics page and diagrams are available at CTstats.