Are you interested in being nominated for a Fellowship of the Learned Society of Wales (LSW) or interested in proposing a colleague? 

LSW Fellows have a connection with Wales, and are elected in recognition of their excellence and outstanding contribution to the world of learning. The Fellowship spans the sciences, humanities, arts and public services and nominations are welcomed from nominees of all cultures, background and ethnicity.

The nomination process is open to academics and professional individuals who meet the nomination criteria.  The nomination is made by a proposer and supported by a seconder, both of whom must be Fellows of the LSW.  Details of the nomination and the election process are on the LSW website. 

The nomination window is now open for this year.  The closing date for applications is the 31 October 2024. Please visit the various LSW web pages and prepare the nomination paperwork by the submission deadline. 

If you feel that help is needed to link a nominee with LSW Fellows or require further information about the support the university can give you please contact Annette Edwards, aee@aber.ac.uk

The Learned Society of Wales  (LSW) annually awards medals to researchers who excel in their field. The medal categories celebrate excellence in several areas of achievements, with further information on each medal at –

• Dillwyn Medals – for Early Career Research Excellence
• Frances Hoggan Medal – for Outstanding Women in STEMM
• Hugh Owen Medal – for Outstanding Educational Research
• Menelaus Medal – for Excellence in Engineering and Technology

If you would like to nominate a colleague or an Early Career Researcher (ECR) please see the guidelines and nomination forms on the LSW web page.

To be eligible for any of the medals, nominees must be resident in Wales, born in Wales, or otherwise particularly connected with Wales.

The deadline for 2024 medal nominations is 5.00pm on 30 June 2024. Each medal has a dedicated committee to assess the nominations and decide who should receive the award.

Winners will be announced in October 2024 and will receive a specially struck medal and a cash prize of £500.

Please read the guidelines before you complete the medal nomination form. If you have any questions, please contact the LSW Fellowship Officer, Fiona Gaskell – fgaskell@lsw.wales.ac.uk. For further information about the LSW Medals, including past winners, visit www.learnedsociety.wales/medals or you can have an informal conversation with Annette Edwards, LTEU aee@aber.ac.uk

Aberystwyth University will be running a two-day Digwyddiad Rhannu Arfer Da – Rhagoriaeth Academaidd on the 2^nd (face to face) and 3^rd (on-line) July 2024. The event will be held through the medium of Welsh only. This event has been made possible due to the Small Grant Project money from the Coleg Cymraeg Cenedlaethol.

The aim of the two-day event is to present papers under the theme of Teaching Excellence – for example:

• Learning and Teaching
• Dysgu trwy gyfrwng y Gymraeg
• Student Support
• Supervision
• Personal Tutoring

The academic papers will be an opportunity for staff across Wales to present their research, under the theme of academic practice – through papers, posters, panels etc. Presentations at the event are welcome from anyone teaching from staff to PhD students.

The Call for Proposals, at the following link Galwad am Bapurau – Digwyddiad Rhannu Arfer Da (jisc.ac.uk)  asks for submissions of no more than 500 words, through the medium of Welsh. We welcome contributions to the event in the form of:

• 20 minutes presentations
• 45 minutes presentations
• An individual or a group presentation
• Posters from individuals or groups
• Sharing good practice Panels

The deadline for these proposals is midday on Wednesday 27 March 2024.

I would be grateful if you could share this more widely with colleagues who maybe in interested in attending this event. 

If you would like to discuss anything further, please do not hesitate to contact me.

Annette Edwards (aee@aber.ac.uk)  01970 622386

Tuesday 13^th February 2024

12.30 – 1.30pm with hot drinks and Welsh cakes available throughout.

Location: Research Dialogue Hub, Visualisation Centre, Penglais Campus.

Tŷ Trafod Ymchwil | Research Dialogue Hub – The Dialogue Centre (aber.ac.uk)

The Learned Society of Wales would like to invite you and a guest to join us at a drop in ‘meet and greet’ session being held at Aberystwyth University on Tuesday 13^th February 2024.

Tea, coffee and light refreshments will be served and you are welcome to join us for as long as you wish between 12.30 and 1.30pm.

You will be able to meet and talk to staff from the Learned Society including Olivia Harrison (CEO) and Helen Willson (Strategic Engagement Manager) as well as our University Representatives at Aberystwyth University – Emeritus Professor Eleri Pryse and Professor Iwan Morus.  We will also be joined by the President of the Learned Society of Wales – Professor Hywel Thomas.

It will be an opportunity for Fellows of the Learned Society to come together and for all those who attend to meet others who are interested in research and its impact in Wales as well as network and find out more about the Learned Society of Wales including its work with Early Career Researchers.

Who is this event for?

• Current Fellows of the LSW
• Anyone interested in research in or about Wales and its impact on policy
• People interested in learning more about becoming a Fellow of the LSW
• Early Career Researchers who would find benefit from joining an interdisciplinary network to engage with and learn from

You can find out more about the LSW and our work here. This is a drop-in session and there is no obligation to sign up or formally accept this invitation.  However, we would appreciate an indication of numbers so If you know you’ll be coming along or if you would like further information please email us on lsw@wales.ac.uk

Sara Childs will be delivering two workshops over the coming weeks based on the findings of ongoing research on trauma-informed communication. Aberystwyth University is committed to becoming one of Wales’s only two trauma-informed universities along with Wrexham university. We are currently in the self-assessment phase of a two-year project, of which the next phase will identify individual projects for enhancing our trauma-informed approach. In parallel, sessions are being offered to the community which raise awareness of trauma-informed approaches.

The upcoming workshops will provide an opportunity for those engaged in teaching, or roles that involve direct contact with students, to develop their practice to incorporate this ground-breaking research.

Towards a trauma-informed approach – theory and reflective practice Part 1

Date: 5/12/23 15.00-16.00

Location: Hugh Owen E3

Towards a trauma-informed approach – theory and reflective practice Part 2

Date: 12/12/23 14.00-16.00

Location: Hugh Owen E3

The following was sent as an email to all staff from Prof. Tim Woods, Pro Vice-Chancellor Learning, Teaching and Student Experience, on 25^th September.

“Dear Colleague

As discussed at the Academic Board on 13^th September 2023, the university has decided to turn off the Turnitin AI Detection tool as of 30^th September 2023. The decision was based on experience with the tool across the higher education sector, especially statistics that seem to demonstrate a high incidence of false positives and the anxiety that this induces for students.  

Generative AI has already become pervasive. It is becoming increasingly embedded in the tools we provide for staff and students such as Office 365 and Blackboard, as well as tools such as Google that are widely used by the general public. It isn’t feasible to ban the use of these tools, so we need to find ways to help students use Generative AI ethically and effectively for real learning, not cheating.  

The promotion of AI literacy for both staff and students has emerged as a key agenda across the higher education sector. A key principle is for staff to be transparent with students about the rationale behind assessments, how they help students learn, and what staff expect from their students. Students, in turn, should apply critical thinking if they use AI tools and be transparent in their submitted coursework about how and where they used such tools. This includes the use of tools such as Grammarly or Quillbot that may have been recommended for students with specific learning differences, for example. 

Please encourage your students to view the new LibGuide created by the Academic Engagement Team in Information Services: Utilising AI in the Library: A Student’s Guide: What is AI? The AI and Your Studies page in the LibGuide was created by the Gen AI Working Group and features video clips highlighting practical guidance on ethical and effective use of AI. A session on Using AI for Good will be offered on 6^th November as part of the Digital Skills Festival.  

Guidance for staff can be found on the LTEU’s workshop materials Generative AIpage, with guidance created by the Gen AI Working Group and links to selected authoritative sources. The staff document will be updated shortly with additional details on how to identify red flags when marking. 

Please see the CPD booking page for upcoming Gen AI training sessions for staff and discussion forums that are open for staff and students together. 

If you have any questions about marking or learning design in connection with AI, please contact the LTEU.  

Best wishes Tim”

This blog post is written by Generative AI Working Group members. 

The landscape for learning and teaching in the age of Generative AI has been developing rapidly. As staff will be aware, the UAP regulation has been updated to address the use of AI in student assessment. The UAP Form and penalty table have been updated to include ‘Presenting work generated by AI as if it were your own’ (approved by Academic Board March 2023). 

• Regulation on Unacceptable Academic Practice  
• Template Form: See section 3.13 

A Generative AI working group, chaired by Mary Jacob, was created in January 2023 to coordinate university efforts. Please see Generative AI for current guidance and resources. We are designing training materials for staff and students that will be available well before next academic year. 

Advice for marking 

On 3/4/2023, Turnitin enabled its AI detection tool. At present, staff can see the ‘AI Score’ but students cannot. This may change if Turnitin updates the tool later in the year. Please see Launch of Turnitin AI writing and ChatGPT Detection Capability on the LTEU blog and Turnitin’s AI Writing Detection from Turnitin (note that sometimes the same passage can be identified as both AI generated and matching an external source).  

There is a clear consensus among experts in the sector that no AI detection tool can provide conclusive evidence.  

This comes from the QAA, the National Centre for AI in Tertiary Education (sponsored by Jisc), and others. You can find links to this evidence on the Generative AI page, including the QAA recording where Michael Webb from the National Centre explains why this is the case. 

If you face a potential UAP case, your professional judgement is key to making the right call. Here is the best advice we can give departments: 

1. Use the Turnitin AI detection tool in conjunction with other indicators – The Turnitin detection tool can identify red flags for further investigation but cannot provide evidence in itself.  

2. Check sources – Gen AI often, but not always, produces fake citations. These can seem plausible at first sight – real authors and real journals, but the article doesn’t exist. Check the sources cited to see if they are 1) real and 2) chosen appropriately for the assignment. Is the source on topic? Is it the type of source a student would have read when writing the assignment (e.g. not a children’s book used as a source for a business case study)? This isn’t conclusive proof of AI use, but it is solid evidence that the student didn’t do things correctly. 

3. Check facts – Gen AI often produces plausible falsehoods. The text may sound reasonable but include some made-up ‘facts’. Gen AI is not intelligent, but merely a sophisticated predictive text machine, so if you spot something that seems a bit off, check to see if it is a plausible falsehood. 

4. Check level of detail – AI tends towards overly-generic output, e.g. using abstract terms with no concrete definitions or examples. Is the essay or report written in generalities or does it include concrete examples in enough detail to support the conclusion that a student wrote it? Again, lack of detail isn’t conclusive evidence that the student cheated but it can be a red flag in combination with other factors.  

5. Hold an interview to determine authenticity – If you see strong indications of unacceptable academic practice, an interview or panel where the student is asked questions about their assignment may be a way to get conclusive evidence. We know this isn’t feasible at large scale, however. This is a sticky problem not only for our university but across the sector.  

To find out more about Generative AI, see the Weekly Resource Roundup for events and materials, e.g. this article specifically about a study on Turnitin’s AI detection: Fowler, G. A. (3/4/2023), We tested a new ChatGPT-detector for teachers. It flagged an innocent student, Washington Post. Fowler explains how they tested it, what they found, and why it generated the false results.  

In short, if staff don’t see anything suspicious other than the Turnitin AI score, we would recommend against bringing a UAP case forward. There’s too much potential for harm if the student really didn’t cheat.