Teaching Algorithmic Bias in a Credit-Bearing Course

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Titel
Teaching Algorithmic Bias in a Credit-Bearing Course
verantwortlich
Carolyn Gardner
Erscheinungsjahr
2019
Medientyp
Preprint
Datenquelle
LISSA
sid-179-col-lissa
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Zusammenfassung
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.
Sprache
Englisch
DOI
10.31229/OSF.IO/CNB4H