Ji Yun Son, Aleksandra Schilis, and Claudia Sutter (CourseKata)
Abstract
Because generative AI can produce polished final answers without corresponding student understanding, educators are rethinking long-standing approaches to assessment. At the same time, assessment in statistics education is arguably more important than ever: the world needs reliable ways to detect human ability to reason with data. In this interactive session, participants will reconsider the fundamental purposes of assessment in statistics education in an AI-rich world. We will consider examples from CourseKata’s statistics and data science curriculum, including performance-based tasks, student learning profiles, and students’ confidence in their ability to master assessment tasks, as starting points for reimagining what assessment can reveal about learning. Through guided discussion, participants will reflect on which statistical and data practices are essential in the modern world, and how assessment can better support the development of these crucial skills.