Student learning analytics in libraries – thoughts and resources

This post was contributed by Kristin Briney and her team members listed below.

Libraries are increasingly seeking data—qualitative and quantitative—to tell a story about their value to patrons, administrators, and financial stakeholders. With the widespread interest in Big Data throughout society, librarians are asking: 1) what data do we have on student behaviors in our information systems, and 2) how can this data explain their learning outcomes? To answer these questions, librarians are beginning to mine EZproxy logs, eResource interactions by looking at single sign on data, collection histories, instruction and other librarian interactions, and physical building access through ID cards. Published analyses indicate potential correlations between particular types of library usage and retention, time-to-degree, GPA, and graduation rates.

As well-intentioned as these efforts are, and as important as it is to demonstrate that libraries aid the institutional mission, there are important issues to consider. Systematic data mining—especially of student behaviors and interactions with library resources—raises student privacy and intellectual freedom issues. Additionally, there are also practical questions regarding whether libraries have data management plans that carefully consider data anonymization, deidentification, retention, and deletion. Researchers across seven institutions have come together to develop a research agenda that seeks to answer these questions and more.

Team:

    • Andrew Asher, Indiana University
    • Kristin Briney, University of Wisconsin-Milwaukee
    • Abigail Goben, University of Illinois at Chicago
    • Kyle M. Jones, Indiana University-Indianapolis (IUPUI)
    • Michael Perry, Northwestern University
    • M. Brooke Robertshaw, Oregon State University
    • Dorothea Salo, University of Wisconsin-Madison

References:

    • Jones, K. M. L., & Salo, D. (forthcoming – 2018). Learning analytics and the academic library: Professional ethics commitments at a crossroads. College & Research Libraries.
    • Briney, K. (submitted). Data Management Practices in Library Learning Analytics: A Critical Review
    • Jones, K. M. L., & LeClere, E. (forthcoming – 2017). Contextual expectations and emerging informational harms: A primer on academic library participation in learning analytics initiatives. In P. Fernandez & K. Tilton (Eds.), Applying library values to emerging technology: Tips and techniques for advancing within your mission. Chicago, IL: Association of College and Research Libraries.
    • Briney K, Goben A, Zilinski L. (2017) Institutional, Funder, and Journal Data Policies. Curating Research Data: Vol 1. Lisa Johnston, ed. Association of College and Research Libraries Publishing.
    • Asher, Andrew  (2017)  Risk, Benefits, and User Privacy: Evaluating the Ethics of Library Data.  In Protecting Patron Privacy: A LITA Guide. Bobbi Newman & Bonnie Tijerina, Eds. Pp. 43-56. Lanham, MD: Rowman & Littlefield.
    • Jones, K. M. L. (2017). Learning analytics and its paternalistic influences. In P. Zaphiris & A. Ioannou (Eds.), Lecture Notes in Computer Science, Learning and Collaboration Technologies: Technology in Education (LCT 2017, HCI International 2017) (pp. 281–292). Springer. doi: 10.1007/978-3-319-58515-4_22
    • Rubel, A., & Jones, K. M. L. (2017). Data analytics in higher education: Key concerns and open questions. University of St. Thomas Journal of Law and Public Policy.
    • Goben A, Sapp Nelson M. (2016) Building Your Research Data Management Toolkit: Integrating RDM into Your Liaison Work. Association of College and Research Libraries. http://acrl.libguides.com/scholcomm/toolkit/RDMWorkshop
    • Goben A, Briney K, Zilinski L. (2016) Going Beyond the Data Management Plan: Services and Partnerships. The Medical Library Association Guide to Data Management for Librarians. Lisa Federer ed. Rowman and Littlefield.
    • Rubel, A. & Jones, K. M. L. (2016). Student privacy in learning analytics: An information ethics perspective. The Information Society, 32(2), 143–159.
    • Goben, A., & Raszewski, R. (2015). Research Data Management Self-Education for Librarians: A Webliography. Issues in Science and Technology Librarianship, 82(Fall 2015). https://doi.org/10.5062/F4348HCK
    • Briney, K., Goben, A., & Zilinski, L. (2015). Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies. Journal of Librarianship and Scholarly Communication.
    • Goben, A., & Raszewski, R. (2015). The data life cycle applied to our own data. Journal of the Medical Library Association : JMLA, 103(1), 40–44. https://doi.org/10.3163/1536-5050.103.1.008
    • Asher, Andrew & Lori Johnke (2013). Curating the Ethnographic Moment.  Archive Journal. 3.  http://www.archivejournal.net/essays/curating-the-ethnographic-moment/
    • Asher, Andrew & Lori Jahnke (2013).  Dilemmas of Digital Stewardship: Research Ethics and the Problems of Data Sharing. Research Data Management: Principles, Practices, and Prospects. Council on Library and Information Resources (CLIR).  Pub. No. 160. Available at http://www.clir.org/pubs/reports/pub160/pub160.pdf.
    • Asher, Andrew, Lori Jahnke & Spencer D.C. Keralis (2012). The Problem of Data.  Council on Library and Information Resources (CLIR).  Pub. No. 154. Available at http://www.clir.org/pubs/reports/pub154 .