What do students mean when they say something is “biased”? What do we mean? Over the years, “bias” has made its way into our colloquial lexicon and become a catch-all for discrimination, underrepresentation, opinions, and unexamined statements of fact. This presents challenges for us and our students when they need to evaluate evidence, participate in class discussions, or learn about bias in specific disciplinary contexts. Paradoxically, “bias” gets both over- and underused:
On one hand, bias gets overused when students don’t know how to address it. Students may evoke “bias” as a scapegoat or premature end to an incomplete analysis: “We can’t really say one way or the other because the data is biased.” Qualitative evidence and methodologies may be dismissed out of hand due to their small sample sizes.
On the other hand, bias gets underused when students weigh all information equally: “Well, that’s my opinion.” While we want students to see their classmates’ and their own experiences as valid and warranting deeper reflection, we also want to instill the importance of gathering evidence, recognizing the strengths and limitations of different kinds of evidence, and forming careful, well-supported conclusions.
This session will explore definitions of and approaches to bias in our disciplines by collectively answering questions such as: How do our disciplines define “bias”? How do I personally use the word “bias”? Is bias always bad? What do we do with it? Can we rid ourselves of it; if we can, should we? We will discuss ideas for helping our students think and converse more clearly about information from different sources, sample sizes, and contexts, including their own lives.
Amy Csizmar Dalal, Professor of Computer Science
Victoria Morse, Director of the LTC and Professor of History
Kristin Partlo, Reference & Instruction Librarian
Lin Winton, Director of the Quantitative Resource Center and Lecturer in Biology