Dismantling Assessment Injustice: Reconceptualizing Consequential Validity, Assessment Fairness, and Measurement Considerations in the Professions

Session Type: Symposium

Abstract

Education in the professions hold a vital role to serve the public to deliver fair and defensible assessment systems. However, recent studies in the professions have found evidence of bias, calling for reconceptualizing assessments; they have also called for reexamining foundations in measurement science that have been traditionally served to safeguard assessment practices. This symposium offers conceptual discussions aimed toward dismantling assessment injustice – prompting discussions around consequential validity, fairness, bias, and measurement considerations. This symposium brings together rich discussions around reconceptualizing foundations of validity, fairness, and psychometric approaches to mitigate assessment bias. We aim to open discussions that dismantle assessment injustice and elevate discussions to create fair and equitable assessment systems in the professions.

Sub Unit

• Division I - Education in the Professions

Chairs

• Yoon Soo Park, University of Illinois at Chicago

• Kuan Xing, University of Iowa

Papers

• Rethinking Validity Evidence: Consequential Validity - Danette Waller McKinley, Foundation for Advancement of International Medical Education and Research

• Examining Fairness in Educational Assessment: A Scoping Review of Current Practices - Christy K. Boscardin, University of California - San Francisco; Justin Louis Sewell, University of California - San Francisco; Bunmi Malau-Aduli, James Cook University; Huiju Carrie Chen, Kaiser Permanente Bernard J. Tyson School of Medicine; Monica M. Cuddy, NBME; Dana Larsen, University of California - San Francisco; Mike Cheng, University of California - San Francisco; Martin Tolsgaard, University of Copenhagen; Cees Van der Vleuten, Maastricht University; Karen E. Hauer, University of California - San Francisco

• Psychometric Considerations for Mitigating Assessment Bias - Chi Chang, Michigan State University; Ting Sun, University of Utah

Discussant

• John Davis, University of California - San Francisco