Generative AI and HE assessment: What do we need to research?

By Jo Walton

Would you like to collaborate on something?

There are a lot of fascinating ongoing conversations about the use of generative AI within HE, and especially the issues it raises for assessment. Kelly Coate, writing for WonkHE, characterizes it as a moral panic, but still a potentially useful one:

If in academia we value things like authenticity, integrity, and originality, we need to be able to articulate why those values remain important in the age of generative AI. Doing this can only help students to make meaning from their higher education learning experience – in fact, it’s really what we should have been doing all along.

Our sense is that there are now many particular well-defined questions which could do with being studied in a more rigorous way, to move these conversations forward. How good are educators at identifying AI-generated text? How good are educators at evaluating their own ability to identify such text? What differences emerge across different assessment designs? How about different disciplines? If AI is deliberately included in the assessment, how accurately can assessors evaluate whether it has been used appropriately? How does the variation in grades assigned compare across non-AI-asssessed work and various types of AI-assisted work? These are all questions we can address from our own experience and miniature experiments. But it would be valuable to conduct some studies at scale, and have some data to debate.

SHL Digital would be keen to hear from colleagues, at Sussex or beyond, who are working on these issues or would be interesting in collaborating. Get in touch with j.c.walton@sussex.ac.uk.

What is a Research Software Engineer (RSE)?

by Elena Dennison, Programme Manager, SHL Digital.

If I had a penny for each clear answer I have been given when asking that question, I would be penniless. So having no pennies to lose, I approached our own RSE, Dr Nic Seymour-Smith and asked him to give me some examples of the types of work he gets involved with at Sussex Digital Humanities Lab at the University of Sussex.

Nic explains that the Research Software Engineer (RSE) role seeks to collaboratively combine professional software expertise with an understanding of research. In this context, to understand what an RSE can and can’t provide it is important to understand the meaning of ‘Research Software’ vs ‘Software in Research’.

‘Research Software‘ understood as source code files, algorithms, scripts, computational workflows and executables that were created during the research process or for a research purpose.
vs
‘Software in Research‘ understood as software components (e.g., operating systems, libraries, dependencies, packages, scripts, etc.) that are used for research but were not created during or with a clear research intent.

 as defined by Barker et al (2022) in the “FAIR for Research Software Principles”.

This differentiation may vary between disciplines and will also vary between individual RSEs, whose backgrounds and experience are as varied as the multitude of research fields that exist in academia.

Working with the particular needs of SHL Digital as a research environment that recognises the vital role of good practice in software and data management, Nic’s RSE role will also facilitate the development of those practices with a focus on reproducibility, reusability, and accuracy of data analysis and applications created for research.

Nic can work together with researchers working within SHL Digital’s remit to develop the technological aspects of funding proposals, ensuring that adequate time, funding, and human resources are assigned to the development of software and hardware components of the project according to best development practices.

Nic can also directly lend his expertise to funded proposals, by being included as an RSE resource in a project. Nic has a broad range of experience in the development of software and hardware solutions, including for example: data analysis and visualisation; multimedia interactive digital software and artworks; interactive mechanical installations; and electronic engineering.

Can I get a penny now?

What we talk about, when we talk about apocalypse

• Jo Lindsay Walton, Sussex Digital Humanities Lab, University of Sussex
• Polina Levontin, Centre for Environmental Policy, Imperial College London

‘The world is ending’, ‘the Earth will be uninhabitable’, ‘humans are going extinct’, ‘we are f⸻’. These are not uncommon sentiments when climate change comes up in university seminar rooms, often accompanied by nervous laughter. Against a background of rising eco-anxiety, how do we talk with students about climate change?

As universities move to embed sustainability across curricula, climate change is coming up more frequently. Educators in fields far removed from Earth Sciences may find themselves grappling with the complexities of climate science. Should we take these despairing statements seriously … and when and how should we counter them?

First, let’s be clear. It is very unlikely that the whole planet will become uninhabitable for humans any time soon. While the risks associated with climate change remain extremely high, the IPCC (the global body responsible for climate science) has lowered its upper bound predictions from about 5℃ to about 3℃, largely due to progress on renewable energy. The current median estimate of IPCC Earth Systems models is 2.2℃.