How could libraries be more involved in the learning analytics programs of their institution? This was a question explored by Megan Oakleaf, Associate Professor, Director of Instructional Quality, at the School of Information Studies at Syracuse University and PI of the Library Integration in Institutional Learning Analytics (LIILA) project. An extensive report was recently issued at the conclusion of this study. It is must reading for anyone involved in learning analytics, whether from the library or other units that might partner with the library on activities.
I was very pleased to serve on the Advisory Board of this project.
To give you an idea of the content of the report, I’m including below the abstract and a portion of the Executive Summary.
"The Library Integration
in Institutional Learning Analytics (LIILA) project, funded by the
Institute of Museum and Library Services, convened three meetings with
academic library administrators, reference and instruction librarians,
systems librarians, library technology administrators, library
association leaders, and IT administrators as well as learning
analytics, library vendor, and learning standards representatives to
increase academic library participation in higher education learning
analytics and prepare academic librarians to engage in this important
use of data to support student learning and success.”
"Finally, the LIILA project yielded ten “next steps” for moving forward in this arena (section 6.0). These next steps include: 1. increasing awareness of and discussion about the role of libraries in institutional learning analytics both within the academic library community and among institutional participants in learning analytics; 2. investigating current library data practices and committing to transparent communication about the ways in which data is gathered, maintained, stored, secured, and used within libraries; 3. communicating and negotiating data rights with library vendor and institutional partners; 4. situating learning analytics among other assessment approaches as a tool for student learning and success support; 5. including libraries in learning analytics conversations at the institutional level; 6. identifying and analyzing questions or problems that require a learning analytics approach; 7. envisioning the contributions that library data makes to developing a holistic picture of student learning and success; 8. exploring interoperability standards that enable disparate information systems to connect in real time; 9. identifying and prioritizing user stories linking libraries and student learning and success that merit further development; and 10. pursuing pilot studies that investigate the feasibility of developing library user stories into achievable integrations of library data into institutional learning analytics."
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