The ever-developing landscape of modern technology has enabled impressive advances in the delivery of teaching in higher education. However, recent changes are so fast paced that educators are struggling to find an effective, pedagogically sound way of handling these advances in their teaching and assessment. Technologies such as version control (e.g. GitHub), generative AI (e.g. ChatGPT), and modern machine learning techniques have quickly gained traction to great effect in recent years. With this increase in prominence also comes a demand for knowledge of these skills in the industrial and academic workplace, and the need to expose both staff and students to such practices.  

In this session, we will discuss our experiences in sharing such knowledge with both student and staff learners, detailing some of the pedagogical challenges and considerations of integrating modern practices into the established statistics curriculum. We will discuss how to teach and integrate version control into modern courses in statistics, and look into how best to respond to ChatGPT in the context of online and lab-based assessments. We will talk about how to improve staff knowledge of modern technologies and how we can help them adjust their teaching practises to account for changes in the technological landscape. We will discuss these challenges in more details through an interactive discussion and look at how educators can continue to adjust to technology in the future. 

We will have three 20-minute talks, with 5 minutes for questions following each talk. There will then be an open discussion around the use of new technologies in statistics education, particularly around how to incorporate learning of both students and staff and challenges in assessment design and implementation. The open discussion session will be facilitated using interactive polling tools such as Mentimeter.