The rapid advancement of generative AI systems—capable of producing valid and valuable solutions for assignments in project-based classes that sometimes are better than the solid work of students—poses significant challenges for education.
Assignments are increasingly unreliable indicators of true understanding and learning. Proper assessment of such assignments becomes increasingly challenging.
This is particularly important, in the context of online education, where there’s no way of monitoring the students during the work on such tasks without severe privacy intrusions, but also in regular on-campus contexts, where students also often finish their projects at home rather than during their on-campus stays.
Drawing from teaching experience, the session will explore effective strategies for assessing authentic projects and collaborative work, with special attention to distributed online classrooms. Key challenges to be addressed are, how to assess individual contributions within team projects, ways to evaluate learning when AI tools are ever-present, and designing assessments that focus on processes rather than products.
