ALA Unit/Subunit: ACRL
Meeting Type: Program
Cost: Included with full conference registration.
Higher education institutions have greatly increased pressure on their libraries and librarians to demonstrate quantitative impact of their resources, staffing, collections and programs in relation to learning outcomes, student success and student retention. This is built on a Big Data toolkit, which calls for warehousing large quantities of data for various analytical purposes. Specifically, this requires identifiable student data and information. While anonymized data mining can provide powerful insights, it doesn't support the purported major goal of learning analytics, which is targeting individual students.
This reliance on one-to-one identified student information raises serious and wide-ranging moral issues and ethical quandaries for librarians. Patron privacy and intellectual freedom has been part of our professional code of ethics since 1939. While we already are navigating issues with vendor privacy, the learning analytics movement goes beyond student resource monitoring to planned intervention.
In addition, learning analytics creates practical questions: identifying what quantitative data might be captured; what systems should be used to capture and warehouse it; when data is used for overall assessment or individual intervention, shared with campus, shared beyond campus; and what library or institutional policies affect any data captured.
This presentation will cover the ethical and practical challenges in the learning analytics movement. It will also review current data handling procedures against best practices for maintaining data security and privacy. Presenters will identifying gaps in understanding how libraries balance institutional/library administration demands with patron privacy and discuss plans to start filling those gaps.