How might GenAI change assessment in higher education?

Dr Sarah Bowden, Reader in German and Medieval Studies; Pro Vice Dean (Assessment), Faculty of Arts and Humanities

In the previous activity, you explored some ways that generative AI could enrich teaching and learning.

In this activity, you will examine some of the immediate and longer-term potentials of generative AI in student assessments, marking and feedback. It contributes to your achievement of one of the course learning outcomes: describe the key capabilities, limitations, challenges and opportunities of generative AI in higher education teaching, learning, feedback and assessment. More specifically, by the end of this activity, you will be able to: 

• Outline key issues around academic integrity and assessment in higher education in the age of AI.  
• Describe how generative AI could impact on assessment design, marking and feedback. 
• Discuss issues of authorship, identification and detection. 

In this step, you will hear from an academic about what the development of generative AI might mean for assessment in the coming years.

In the video for this step, Sarah talks about some of the challenges posed to assessment by generative AI. She also thinks about the implications of these challenges and what assessment in higher education might look like in five or even two years’ time.

When you have completed this step, you will have considered what generative AI means for the ways we assess in higher education. In the next step, you will look at how you might reevaluate assessment design in the light of the opportunities provided by generative AI.

Join the conversation

Drawing on the video prompt, brainstorm some new forms of assessment for your discipline. Ask yourself:

• Are they vulnerable to generative AI?
• Could they respond positively to generative AI?
• How do they move student learning forwards and develop key skills?