Abstract
Information literacy instruction has become increasingly nuanced with the widespread adoption of critical approaches to teaching and the ACRL Framework. Librarians are already teaching information evaluation strategies, however, more work can be done in the area of understanding algorithmic decision making and bias. This column describes how a public university integrated lessons on algorithmic bias into a credit-bearing information literacy course for a general undergraduate audience. The activities and readings can be adapted to a one-shot instruction environment and the collaborative process for designing the curriculum is also shared.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
