Towards Fair and Diversity-Appropriate E-assessments

The use of e-assessments has gained significant prominence in educational settings as they offer a range of benefits such as improved scalability, accessibility, and cost-effectiveness. This chapter discusses the possibilities of addressing diversity in educational e-assessments. We propose a workaround using assessment analytics to identify test items prone to diversity-related performance differences. Based on this, we offer theory-guided suggestions on how diversity-appropriate assessments could be realized. In a proof of concept using data collected in a mock e-assessment, we demonstrate a workaround for identifying potential diversity biases on the item-level with small sample sizes. To put this into practice, a technical infrastructure using Experience API is proposed. Based on established cognitive theories focusing on learning processes, it is outlined how the flexibility of e-assessments regarding item presentation can be used to address the needs and preferences of diverse test takers. The chapter concludes by highlighting the potential of e-assessments to address diversity and proposes perspectives for research and practical application.