CREDS Research Sprints 2026

CREDS is delighted to announce three ‘CREDS Research Sprints’ projects funded for 2026. Congratulations to all involved. We look forward to hearing about each project in the CREDS 2027 seminar series!

Digital Twinning to Support Transdisciplinary Learning in School Education

Lauren Knussen, Annnie Agnew, Richard Blows, Rebecca Di Corpo

Our aim is to explore the potential of digital twinning technologies to support students’ understanding of historical sites and contemporary life in and around the site.  Digital twinning technologies accurately recreate historical sites using data from archaeological excavations, contemporary artistic rendering, astronomy, geology and other sources and allow the depiction of historical sites as they were at the time they were used, but also allow the structures on the site to be mapped on to modern day 3D maps. 

Designing AI-Driven Machine Translation Tools for Academic Language in Multilingual Higher Education 

Anika Harju, Camille Dickson-Deane, Amara Atif

The aim is to analyse the learning‑technology design barriers that sustain instruction when English is not the students’ first language.  The existing   Artificial Intelligence (AI)-driven translation technologies /tools (e.g., Microsoft Bing, Google Translate, Deep Learning, and ChatGPT) that are used to convert different languages to English provide errors and misaligned meanings in discipline-specific fields. These tools use engines that translate between languages, and this project aims to address these engines. The engines are made up of programming code that can be finessed based on disciplinary knowledge, and the code is tied to tools presented in a learning management system (LMS). The project aims to train a model to make disciplinary knowledge relevant through a proof-of-concept.   

Preparing the Digital Teacher: A Co-Designed Professional Development Framework for AI-Driven and Emotion-Sensitive Pedagogical Tools

Amara Atif, Mais Fatayer, Hyunmin Lee, Dongyeon Kim

This project aims to investigate, co-design, and openly disseminate a Professional Development (PD) Framework that equips educators to critically and confidently integrate AI-driven and emotion-sensitive tools into their teaching practice. Such tools are increasingly present in higher education contexts: from AI-generated feedback systems and learning analytics dashboards that flag at-risk students, to sentiment analysis of discussion board posts and early alert systems that combine behavioural and affective data signals. Yet educators are rarely prepared to use these tools critically, equitably, or responsibly. 

Specifically, the project addresses three research questions: 

RQ1-What are educators’ current levels of readiness, confidence, and concern regarding AI-driven and emotion-sensitive pedagogical tools? 

RQ2-What contextual, institutional, and personal factors shape teachers’ adoption of these tools?

RQ3-What does an effective, inclusive PD framework look like when co-designed with educators rather than for them?

Each question builds on the last - mapping the problem, understanding its roots, and designing a solution that is grounded in real educator experience rather than assumption.