As Collection Assessment Librarian, here is what I could do with this data:
- Associate resource usage (print and online) with grades, degree completion, schools, years in the program, on- versus off-campus, student backgrounds (like locations of high schools or community colleges, family income, work loads, ages)...
- Associate collection coverage with courses much more easily than the manual or semi-manual process we do now.
- Demonstrate to faculty any disparities of usage of resources assigned (this refers to the copyright case in Georgia where it was found that they were not in violation of copyright for many of the items posted online because they were simply not used!)
- Determine how different or how similar different student groups are in terms of library usage.
- Identify the groups of students or faculty who never use the library in order to conduct additional research to find out what they do use and how we could reach them better.
This kind of connection of student and school measures with resource usage measures is becoming more prominent in other countries, but less so here in the United States.
This line from the video, "At the heart of Library Cube is the Student Number," points out the key reason, I believe. Concerns about privacy have led to policies that unnecessarily restrict the sharing of key data. There are ways to make the data effectively anonymous, but there is still great reluctance. Technology is another obstacle, but one that should not be hard to overcome. Our library is veering ever so slightly in this direction, starting with our face-to-face instruction sessions and some courses that are taught largely through Blackboard. I hope that the results will convince the decision-makers that this method can and should be used to help make informed decisions while not infringing on students' rights and not imposing unnecessary work on the data gatherers.