Collaborative Innovation Grants (CIGs)
Collaborative Innovation Grants (CIGs)
Each year, DCAD fund a number of projects through its Collaborative Innovation Grants. This grant scheme is designed to support staff across Durham University to develop innovative and inclusive learning and teaching approaches to enhance student learning and success, and to disseminate good practice across the institution and beyond.
More information on Collaborative Innovation Grants (Durham University internal access only) can be found here.
Current and recent projects are listed below.
Understanding students experiences and attitudes towards Generative AI from an EDI perspective : The potential benefits for Teaching and Learning.
Trevor James (Psychology)
Rachelle O’Brien & Candace Nolan-Grant (DCAD)
The purpose of this project is to argue that to develop innovative and inclusive teaching and assessment using generative AI, we first need to take an inductive, ground-up approach, understanding how students use generative AI and how this relates to pedagogy. We further argue that to develop inclusive teaching and assessment using generative AI we need to understand how AI intersects with EDI and learning. For this reason, the project has a strong focus on the experiences of neurodiverse students, international students, and BME background students.
Through this project we aim to address the following research questions:
- What is the prevalence of AI use by students in Higher Education?
- What is the level of awareness in the student body towards generative AI and its functionality?
- Do students see AI as ‘cheating’ or ‘teaching’ and what is the general attitude towards AI in the student body?
- How do students currently use AI in their learning and does this vary between home students and international students?
- How does AI intersect with EDI; more specifically, do certain groups of students potentially benefit from AI more than others, e.g., neurodiverse students and BME students.
- How does AI interact and relate to well-established pedagogical variables related to learning and academic success, e.g., self-efficacy and student motivation (Zimmerman, 1995)
Making an Artificial Intelligence-powered chatbot for student support and personalised learning.
Arin Mizouri (Physics)
Ross Parker (DCAD)
The project aims to design a prototype chatbot that can assist in the instruction of a first-year physics module titled “Discovery Skills in Physics”. The course covers a wide array of topics, such as laboratory skills, programming, data analysis, scientific presentations, and scientific writing, all of which are critical for advancing past the first level of study. Given the broad subject matter and diverse student cohorts, it is a significant challenge for lecturers and laboratory demonstrators to promptly respond to student queries. This module involves 13 lectures presented by four different lecturers and weekly laboratory sessions. Feedback has revealed a desire for greater consistency in the lab support provided, given the varying levels of experience of the lab demonstrators.
How can ChatGPT support the development of target language writing-skills in Modern Foreign Languages in Higher Education?
Aziza Zaher (MLaC)
James Youdale (DCAD)
Madeleine Jablonowska (Student)
This study proposes to explore how Generative AI can support writing skills, feedback and academic advising through ‘assessment for learning’ (Boud, et al, 2010) activities in the MFL context, focusing particularly on skills development such as reflection, reasoning, critical thinking, prompt generation and digital skills. This study will seek to place a particular focus on the new knowledge that students generate when they compare their current knowledge and competence against reference information (Nicol & McCallum, 2021), with students completing prescribed tasks both with, and without, the use of Generative AI, and receiving both instructor-authored and Generative AI authored feedback.
Using Artificial Intelligence (AI) to enhance critical thinking: are students ready for this?
Mathilde Roger, Helen Thompson, Gillian Campling (Biosciences)
Ross Parker and Paul Finley (DCAD)
Melody Mu (Student)
The purpose of this project is to explore how an AI-powered language model can be used to facilitate inner feedback by comparison and develop student’s critical thinking skills. Student expectations and experiences of using Generative AI will be evaluated as part of the project. This project will encourage and support academics from the Biosciences department to use AI tool for Teaching, Learning and Assessment (TLA). Academics will be encouraged to use AI to generate exemplars and develop activities that explicitly promote self-feedback by comparison. It will also assess students experience and expectation in using AI tools for TLA in HE at the end of the academic year via survey. The aim is then to develop resources to facilitate the use of AI within the institution and further: guidance and support to use it as academic and as a student.
Making fieldwork accessible with 3-D outcrop models generated from drone collected data
Chris Savile (Earth Sciences)
Ross Parker (DCAD)
Abbie Doherty (Student)
The purpose of this study is to explore the use of drones and 3-D modelling technology as a way of creating more inclusive field trip materials for Earth Sciences students. This will be used to support a virtual pathway option through the field work module GEOL1051 and enhance the accessibility of Field work in the other modules that use fieldwork, while being not exclusively fieldwork based.
The project will develop digital 3-D models of field trip sites used in Earth Sciences and evaluate students’ experiences of using these models, using a combination of surveys and focus groups. This will lead to the creation of guides to using the 3D models for both staff and students.
Generative AI and the Future of Academic Law Degrees.
Emma Milne (Law)
Candace Nolan-Grant (DCAD)
This project will aim to obtain a multi-perspective view on the role of generative AI in undergraduate and postgraduate law degrees, to inform the approach of Durham Law School and other UK Law Schools to student and staff use of generative AO in teaching and learning. The project objectives are:
- To understand the views and perspectives of students in terms of whether and how they should make use of generative AI in their studies and assessments.
- To understand the views and perspectives of law academics in terms of whether and how generative AI should be used in teaching and learning, by students in their studies and assessments, and also by academics in the development of teaching materials and assessments.
- To understand the views and perspectives of legal professionals/law graduate employers on the role of generative AI in legal practice and therefore the role generative AI should play in LLB and LLM degrees.
- To examine the current abilities of large language models to respond to DLS assessments.
- In light of the findings from objectives 1 to 4, to offer recommendations in terms of how UK Law Schools should respond to the developments in generative AI and academic law degrees.
Student response to a cross-curriculum approach to climate education.
Kim Bouwer (Law)
Julie Mulvey (DCAD)
Climate change is a dynamic issue requiring a concerted and consistent response across a range of institutions and levels to respond to its challenges (Bouwer, 2015); it is also legally disruptive to existing legal doctrines and frameworks (Fisher et al., 2017). In light of this, climate conscious lawyers should understand how environmental considerations can be relevant in many areas of law from tort to land to human rights (Bouwer, 2015).
As a result, legal education providers have a responsibility to ensure students are receiving sufficient climate education to equip them to bring a climate conscious approach to their future practice (Preston, 2021; Bouwer et al., 2022). Previous empirical studies have suggested that students want to be taught climate law and have argued it should be part of their required learning in the LLB degree (Bouwer et al., 2022; drawing on Ong, 2016). This has formed the basis of the climate education project (CEP) at Durham Law School (DLS), which has sought to ‘naturally’ incorporate climate education in the compulsory modules of the law degree (Bouwer et al., 2023). It is now necessary to evaluate how the students received this.
The project has overlapping internal / external and pedagogical / scholarly focuses. The project seeks to assess student responses to the CEP, and to evaluate the cross-curriculum approach and pedagogical approach(es) taken in CEP – this will support further innovation before CEP moves to the consolidation phase. This also has potential to inform cross-curriculum approaches to sustainability education in other disciplines.
Embedding neurodiversity-affirmative pedagogy within academic staff training at Durham University.
Debbie Riby (Psychology / Centre for Neurodiversity and Development)
Sam Nolan (DCAD)
Jess Loudon, N.A. Roza, Clara Springman (Students)
The number of neurodivergent university students is on a rapid upwards trajectory, and it is crucial that academic staff have sufficient knowledge to provide an inclusive learning environment/ experience that meets the needs of all students, including those who are neurodivergent. Such work is essential for meeting the expectation of the Principles for Teaching, Learning and Assessment- Inclusive Learning Environments, as well as more widely, the Education Strategy and supports the core objectives of the Access & Participation Plan (APP).
The purpose of this project is to develop, run and begin to evaluate a new online training module for academic staff to increase their knowledge and awareness of neurodiversity and its relevance to teaching and learning.
Trauma-Informed Teaching Pedagogy : Embedding student voice into the ‘Principles’ for Higher Education classroom.
Charmele Ayadurai (Finance)
Sumetha Karthigeyen (DCAD)
Viju Radhakrishnan (Student)
The project aims to embed student voice into the existing Trauma-Informed Teaching Pedagogy (TITP) framework. The framework was initially applied in a PG classroom, Business Economics and Accounting, during the pandemic. Student feedback suggests that while some principles were easily understood and applied, the remaining principles (1,5,6,7) posed a challenge.
The project will:
- Provide a platform for students to work as partners to develop classroom implementation plans that are better aligned to support students’ needs based on the TITP principles
- Develop high quality, accessible instructions to support students to better engage with the framework
- Create a set of instructions for staff to embed TITP in the classroom, focussing on students’ well-being
- Assess the value and outcomes of this project
- Develop resources to facilitate within institution and further guidance for staff members to incorporate the framework and classroom implementation plans in their departments.
AI and Employability : How can Generative AI support students in the recruitment process.
Jessica O’Brien (Careers and Enterprise)
Sumetha Karthigeyen (DCAD)
Agnibeena Ghosh (Student)
The purpose of this project is to evaluate how students can use Gen AI ethically and effectively to create CVs and cover letters during the employment recruitment process. The initial research will focus on work experience applications for internships and placement years, but it is anticipated that the work will transfer to support students in the graduate recruitment process as well.
The objectives of the project are to:
- Determine effective ways to use and prompt AI when writing CVs and cover letters
- Empower students with digital skills to use Gen AI ethically and effectively in their application documents
- Create resources for students to reference when using AI to support their application documents.
AI-Generated images as a stimulus to the engagement and cognition of literary texts.
Alistair Brown (English),
Jin Huang (MLAC)
James Youdale and Mark Childs (DCAD)
Tilottama Chowdhury (Student)
Virtual Reality (VR) has been used extensively in experiential teaching and learning, such as to simulate healthcare situations (Jiang et al., 2022) or for virtual field trips (Klippel et al., 2019). However, VR has been less used in teaching and learning in Arts and Humanities, especially in text-based rather than place-based subjects such as English and Translation Studies. The investment to produce content for VR has not yet been provably paid off by the pedagogic returns. This project pioneers a possible way to bridge this gap, leveraging AI to cheaply generate VR-based content.
In this project, we exploit emergent AI technologies to cheaply generate 360-degree images that visually represent passages taken from a literary text in English (chosen by the academic team and student advisors). Participants will listen to a short passage from the text, viewed with the accompanying imagery in VR (for example, a student might view a VR rendering of Sherlock Holmes’s study, while hearing the representation of that space in language). This experience will be compared to just listening to an audio version of an equivalent passage from elsewhere in the text, and reading a third equivalent passage in traditional print. Through this, we seek to understand:
- Do visually enhanced audiobooks, viewed in VR, better enable English Literature students to engage with, comprehend, or critically interpret the original text compared to audio alone or print reading?
- Do these same modalities assist translation students in gaining a deeper understanding of the original text, resulting in a lower cognitive load during translation and higher-quality translation outcomes?