Abstract

The success of generative AI technologies is dramatically reshaping the landscape of the modern working world, compelling educators to rethink how we design relevant assessments and learning outcomes. Traditional assessment methods, which can often be bypassed using generative AI, may no longer adequately prepare students for the dynamic and collaborative environments they will encounter in their professional lives. Here, we explore the need to redesign assessments to align with these evolving demands, focusing on a practical examples from our Python programming courses.

In this talk, we will discuss the critical shifts required to maintain academic integrity and pass on relevant skills to students entering a generative AI technology-enabled world. We present the changes we made to our assessments, any differences in student’s performance and experience, issues that arose, and the methods they were required to use. We will discuss innovative assessment changes to encourage deeper learning, critical thinking, and problem-solving skills, which are essential in today’s technology-driven workplace.