What Role Can University Libraries Play in Institutional Analytics?

min read

College and university libraries can provide important contributions to institutional efforts to use learning analytics to improve student learning and success.

2 wooden figures wearing graduation caps and standing on an open textbook.
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Two years ago, I asked you to consider what voices might be missing from your institutional learning analytics initiatives. On many campuses, one answer to this question is the academic library. But how can academic librarians be included in institutional discussions and deployments of learning analytics?

A new white paper from the Library Integration in Institutional Learning Analytics (LIILA) grant (funded by the Institute of Museum and Library Services) provides a foundation for discussions about the role academic libraries may play in learning analytics efforts at the institutional level. Based on a series of three National Forum events, this white paper envisions library involvement in learning analytics, including describing facilitators and obstacles to library engagement, and suggests next steps regarding how college and university libraries can participate in learning analytics.

First, eight strategies were identified and deployed to help librarians and interested institutional partners:

  1. Identifying problems to solve and stakeholders to support
  2. Articulating questions that library data may answer
  3. Imagining future actions
  4. Considering facilitators of library engagement in learning analytics
  5. Anticipating librarian roles in learning analytics efforts
  6. Envisioning beneficial scenarios
  7. Reflecting on existing data
  8. Creating user stories

Second, the LIILA project white paper pinpointed both facilitators of and obstacles to library involvement in learning analytics. Facilitators include intersecting pressures that either propel or enable higher education institutions to commit to learning analytics initiatives, such as:

  • Responsibility to provide quality experiences for students, to support student learning and success, and to demonstrate the value students receive in exchange for their investment of time, energy, and resources
  • Stakeholder concerns about dropout rates and skyrocketing student debt
  • Accreditation and other accountability obligations
  • Competition among institutions
  • Budgetary pressures
  • Student tolerance of data use, particularly in exchange for support, benefits, or advantages
  • Technological developments to enable analytics
  • The emergence of positive results documented by learning analytics early adopters

Librarians themselves may also serve as facilitators of engagement. Indeed, librarians can become essential partners in learning analytics at an institutional level because of their history of data gathering, knowledge of data practices, commitment to ethical data use, ability to collaborate across institutional silos, potential role as lynchpins in student interventions focused on information use, and emerging corpus of research demonstrating the contributions of library interactions to student learning and success.

A number of obstacles surfaced as well, such as privacy concerns; data concerns related to quality, granularity, and access; and a potentially resistant organizational culture.

Finally, the LIILA white paper offers ten next steps to move forward:

  1. Increasing awareness and discussion of libraries' role in institutional learning analytics, both within the academic library community and among higher education 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 vendors 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 library data contributions in 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, student learning and success that merit further development
  10. Pursuing pilot studies that investigate the feasibility of developing library user stories for achievable integrations of library data into institutional learning analytics

Hopefully the report will stimulate discussion about the pivotal role libraries can play in institutional learning analytics and will enable librarians to take their place among institutional partners using learning analytics to support student learning and success.

Megan Oakleaf is Associate Professor of Library and Information Science and Director of Instructional Quality at Syracuse University.

© 2019 Megan Oakleaf. The text of this work is licensed under a Creative Commons BY-NC-ND 4.0 International License.