Exploring Sources of Bias to Improve the Universal Design of Assessments of Mathematical Problem-Solving Skills

• In Event: (Un)Masking Intersectional Experiences and Concerns in K–12 STEM Education

Abstract

The advancement of standardized assessments of problem-solving skills calls for open-ended, authentic tasks, which can be susceptible to item bias and challenge the fairness of assessments. Framing prototype items for the Problem-solving Measures Grades 6-8 Computer Adaptive Tests as a bounded case, we explored shared understandings by experts of potential sources of bias in middle-school mathematics assessments through the Delphi technique. Assumed lived experience by all, accessibility issues, language use, and stereotypes were among the most prevalent sources of potential bias, as emerged from thematic coding of expert descriptions. These sources place sub-groups of students from certain sociocultural backgrounds (e.g., culture, gender, race/ethnicity) at a potential disadvantage. Implications for item development for equitable K-12 mathematics problem-solving assessments are discussed.

Authors

• Yiyun Fan, Binghamton University - SUNY
  Presenting Author

• Kristin L.K. Koskey, Drexel University
  Presenting Author

• Dara N. Bright, Drexel University
  Non-Presenting Author

• Toni A. May (Sondergeld), Drexel University
  Non-Presenting Author

• Katrina Struloeff, University of Pennsylvania
  Non-Presenting Author