Equitable counts: Inclusive data analysis, data quality, and dissemination

dc.contributor.authorBrckaLorenz, Allison
dc.date.accessioned2025-05-12T16:46:14Z
dc.date.available2025-05-12T16:46:14Z
dc.date.issued2025
dc.description.abstractInstitutional research and assessment that uses quantitative data faces many challenges in ensuring that data practices are equitable and inclusive. Critical approaches to quantitative data challenge traditional models, measures, and analytic processes often used in traditional quantitative research. Although a critical lens can allow us to better find areas of inequity, these approaches can be met with skepticism and misunderstandings. Participants in this session will learn about critical quantitative inquiry and how it can apply to four different areas of IR decision making: data collection, data analysis, assessing data quality, and dissemination of results. We will discuss critiques of traditional assumptions and uses of quantitative data, look at examples for how we can apply critical approaches to our work, and learn about challenges we should anticipate when using critical quantitative inquiry in IR decision making and in sharing critically derived results with others.
dc.identifier.urihttps://hdl.handle.net/2022/33587
dc.titleEquitable counts: Inclusive data analysis, data quality, and dissemination

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
AIR25 equitable counts.pdf
Size:
163.99 KB
Format:
Adobe Portable Document Format
Can’t use the file because of accessibility barriers? Contact us