An Optimistic Outlook on Teaching, Learning and Assessment for Coding With the Emergence of Generative AI

Steven Watterson; Laila Dabab Nahas; Tuğrulcan Elmas; Hebatallah Shoukry; Ozan Evkaya

doi:10.2218/ED.9781836450795

An Optimistic Outlook on Teaching, Learning and Assessment for Coding With the Emergence of Generative AI

Authors

Steven Watterson

Personalised Medicine Centre, School of Medicine, Ulster University

Laila Dabab Nahas

Edinburgh Medical School, University of Edinburgh

Tuğrulcan Elmas

School of Informatics, University of Edinburgh

Hebatallah Shoukry

School of Engineering and Physical Sciences, Heriot-Watt University

Ozan Evkaya

School of Mathematics, University of Edinburgh

DOI: https://doi.org/10.2218/ED.9781836450795.11

Synopsis

You are likely familiar with the fact that students can now generate working code in a matter of seconds with AI. However, you may also worry about what this means for assessments and question the value of your own teaching. This chapter invites you to rethink your approach to teaching and focus on what matters most when teaching students how to code. The authors talk about how Gen AI tools can help with exploration and feedback, while keeping some space for struggle and genuine understanding. They share examples of how to adapt your teaching and assessment without giving up on rigour.

If you are wondering about how to rethink your teaching or assessment approach for students coding with AI, this will be an interesting read.