Inclusive Counts: Critical Data Analysis, Data Quality, and Dissemination

Session Abstract: Institutional 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.

Keywords: critical, equity, inclusion, QuantCrit, CritQuant, data analysis, demographics, data quality